picocreator
commited on
Commit
·
425b411
1
Parent(s):
ce1db6c
llama 7b (v1)
Browse files- lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +252 -0
- lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
- lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +283 -0
- lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
- lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +390 -0
- lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
- lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +548 -0
- lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
- lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +423 -0
- lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
- lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +3 -0
- lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +248 -0
- lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +3 -0
lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b93c4e0fb038c10d2cf39827b6149ac80ae356d0047adb9508e708825de9b461
|
3 |
+
size 5549153
|
lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,252 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"lambada_multilingual": {
|
4 |
+
"perplexity,none": 34.70618327212021,
|
5 |
+
"perplexity_stderr,none": 10.13400692835123,
|
6 |
+
"acc,none": 0.4961769842810014,
|
7 |
+
"acc_stderr,none": 0.07008621640376027,
|
8 |
+
"alias": "lambada_multilingual"
|
9 |
+
},
|
10 |
+
"lambada_openai_mt_de": {
|
11 |
+
"perplexity,none": 52.1774210359345,
|
12 |
+
"perplexity_stderr,none": 3.066701318008749,
|
13 |
+
"acc,none": 0.3842421890161071,
|
14 |
+
"acc_stderr,none": 0.006776720307079438,
|
15 |
+
"alias": " - lambada_openai_mt_de"
|
16 |
+
},
|
17 |
+
"lambada_openai_mt_en": {
|
18 |
+
"perplexity,none": 3.500850622734743,
|
19 |
+
"perplexity_stderr,none": 0.06865018892342145,
|
20 |
+
"acc,none": 0.7308364059771008,
|
21 |
+
"acc_stderr,none": 0.006179172491966779,
|
22 |
+
"alias": " - lambada_openai_mt_en"
|
23 |
+
},
|
24 |
+
"lambada_openai_mt_es": {
|
25 |
+
"perplexity,none": 44.71228931610228,
|
26 |
+
"perplexity_stderr,none": 2.3667778615446906,
|
27 |
+
"acc,none": 0.42751795070832527,
|
28 |
+
"acc_stderr,none": 0.0068923954478686475,
|
29 |
+
"alias": " - lambada_openai_mt_es"
|
30 |
+
},
|
31 |
+
"lambada_openai_mt_fr": {
|
32 |
+
"perplexity,none": 30.92265081458904,
|
33 |
+
"perplexity_stderr,none": 1.6736871487566927,
|
34 |
+
"acc,none": 0.4818552299631283,
|
35 |
+
"acc_stderr,none": 0.006961389291072816,
|
36 |
+
"alias": " - lambada_openai_mt_fr"
|
37 |
+
},
|
38 |
+
"lambada_openai_mt_it": {
|
39 |
+
"perplexity,none": 42.21770457124047,
|
40 |
+
"perplexity_stderr,none": 2.4716268498273224,
|
41 |
+
"acc,none": 0.45643314574034544,
|
42 |
+
"acc_stderr,none": 0.0069394834360396295,
|
43 |
+
"alias": " - lambada_openai_mt_it"
|
44 |
+
}
|
45 |
+
},
|
46 |
+
"groups": {
|
47 |
+
"lambada_multilingual": {
|
48 |
+
"perplexity,none": 34.70618327212021,
|
49 |
+
"perplexity_stderr,none": 10.13400692835123,
|
50 |
+
"acc,none": 0.4961769842810014,
|
51 |
+
"acc_stderr,none": 0.07008621640376027,
|
52 |
+
"alias": "lambada_multilingual"
|
53 |
+
}
|
54 |
+
},
|
55 |
+
"configs": {
|
56 |
+
"lambada_openai_mt_de": {
|
57 |
+
"task": "lambada_openai_mt_de",
|
58 |
+
"group": [
|
59 |
+
"lambada_multilingual"
|
60 |
+
],
|
61 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
62 |
+
"dataset_name": "de",
|
63 |
+
"test_split": "test",
|
64 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
65 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
66 |
+
"description": "",
|
67 |
+
"target_delimiter": " ",
|
68 |
+
"fewshot_delimiter": "\n\n",
|
69 |
+
"metric_list": [
|
70 |
+
{
|
71 |
+
"metric": "perplexity",
|
72 |
+
"aggregation": "perplexity",
|
73 |
+
"higher_is_better": false
|
74 |
+
},
|
75 |
+
{
|
76 |
+
"metric": "acc",
|
77 |
+
"aggregation": "mean",
|
78 |
+
"higher_is_better": true
|
79 |
+
}
|
80 |
+
],
|
81 |
+
"output_type": "loglikelihood",
|
82 |
+
"repeats": 1,
|
83 |
+
"should_decontaminate": true,
|
84 |
+
"doc_to_decontamination_query": "{{text}}",
|
85 |
+
"metadata": {
|
86 |
+
"version": 1.0
|
87 |
+
}
|
88 |
+
},
|
89 |
+
"lambada_openai_mt_en": {
|
90 |
+
"task": "lambada_openai_mt_en",
|
91 |
+
"group": [
|
92 |
+
"lambada_multilingual"
|
93 |
+
],
|
94 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
95 |
+
"dataset_name": "en",
|
96 |
+
"test_split": "test",
|
97 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
98 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
99 |
+
"description": "",
|
100 |
+
"target_delimiter": " ",
|
101 |
+
"fewshot_delimiter": "\n\n",
|
102 |
+
"metric_list": [
|
103 |
+
{
|
104 |
+
"metric": "perplexity",
|
105 |
+
"aggregation": "perplexity",
|
106 |
+
"higher_is_better": false
|
107 |
+
},
|
108 |
+
{
|
109 |
+
"metric": "acc",
|
110 |
+
"aggregation": "mean",
|
111 |
+
"higher_is_better": true
|
112 |
+
}
|
113 |
+
],
|
114 |
+
"output_type": "loglikelihood",
|
115 |
+
"repeats": 1,
|
116 |
+
"should_decontaminate": true,
|
117 |
+
"doc_to_decontamination_query": "{{text}}",
|
118 |
+
"metadata": {
|
119 |
+
"version": 1.0
|
120 |
+
}
|
121 |
+
},
|
122 |
+
"lambada_openai_mt_es": {
|
123 |
+
"task": "lambada_openai_mt_es",
|
124 |
+
"group": [
|
125 |
+
"lambada_multilingual"
|
126 |
+
],
|
127 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
128 |
+
"dataset_name": "es",
|
129 |
+
"test_split": "test",
|
130 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
131 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
132 |
+
"description": "",
|
133 |
+
"target_delimiter": " ",
|
134 |
+
"fewshot_delimiter": "\n\n",
|
135 |
+
"metric_list": [
|
136 |
+
{
|
137 |
+
"metric": "perplexity",
|
138 |
+
"aggregation": "perplexity",
|
139 |
+
"higher_is_better": false
|
140 |
+
},
|
141 |
+
{
|
142 |
+
"metric": "acc",
|
143 |
+
"aggregation": "mean",
|
144 |
+
"higher_is_better": true
|
145 |
+
}
|
146 |
+
],
|
147 |
+
"output_type": "loglikelihood",
|
148 |
+
"repeats": 1,
|
149 |
+
"should_decontaminate": true,
|
150 |
+
"doc_to_decontamination_query": "{{text}}",
|
151 |
+
"metadata": {
|
152 |
+
"version": 1.0
|
153 |
+
}
|
154 |
+
},
|
155 |
+
"lambada_openai_mt_fr": {
|
156 |
+
"task": "lambada_openai_mt_fr",
|
157 |
+
"group": [
|
158 |
+
"lambada_multilingual"
|
159 |
+
],
|
160 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
161 |
+
"dataset_name": "fr",
|
162 |
+
"test_split": "test",
|
163 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
164 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
165 |
+
"description": "",
|
166 |
+
"target_delimiter": " ",
|
167 |
+
"fewshot_delimiter": "\n\n",
|
168 |
+
"metric_list": [
|
169 |
+
{
|
170 |
+
"metric": "perplexity",
|
171 |
+
"aggregation": "perplexity",
|
172 |
+
"higher_is_better": false
|
173 |
+
},
|
174 |
+
{
|
175 |
+
"metric": "acc",
|
176 |
+
"aggregation": "mean",
|
177 |
+
"higher_is_better": true
|
178 |
+
}
|
179 |
+
],
|
180 |
+
"output_type": "loglikelihood",
|
181 |
+
"repeats": 1,
|
182 |
+
"should_decontaminate": true,
|
183 |
+
"doc_to_decontamination_query": "{{text}}",
|
184 |
+
"metadata": {
|
185 |
+
"version": 1.0
|
186 |
+
}
|
187 |
+
},
|
188 |
+
"lambada_openai_mt_it": {
|
189 |
+
"task": "lambada_openai_mt_it",
|
190 |
+
"group": [
|
191 |
+
"lambada_multilingual"
|
192 |
+
],
|
193 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
194 |
+
"dataset_name": "it",
|
195 |
+
"test_split": "test",
|
196 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
197 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
198 |
+
"description": "",
|
199 |
+
"target_delimiter": " ",
|
200 |
+
"fewshot_delimiter": "\n\n",
|
201 |
+
"metric_list": [
|
202 |
+
{
|
203 |
+
"metric": "perplexity",
|
204 |
+
"aggregation": "perplexity",
|
205 |
+
"higher_is_better": false
|
206 |
+
},
|
207 |
+
{
|
208 |
+
"metric": "acc",
|
209 |
+
"aggregation": "mean",
|
210 |
+
"higher_is_better": true
|
211 |
+
}
|
212 |
+
],
|
213 |
+
"output_type": "loglikelihood",
|
214 |
+
"repeats": 1,
|
215 |
+
"should_decontaminate": true,
|
216 |
+
"doc_to_decontamination_query": "{{text}}",
|
217 |
+
"metadata": {
|
218 |
+
"version": 1.0
|
219 |
+
}
|
220 |
+
}
|
221 |
+
},
|
222 |
+
"versions": {
|
223 |
+
"lambada_multilingual": "N/A",
|
224 |
+
"lambada_openai_mt_de": 1.0,
|
225 |
+
"lambada_openai_mt_en": 1.0,
|
226 |
+
"lambada_openai_mt_es": 1.0,
|
227 |
+
"lambada_openai_mt_fr": 1.0,
|
228 |
+
"lambada_openai_mt_it": 1.0
|
229 |
+
},
|
230 |
+
"n-shot": {
|
231 |
+
"lambada_multilingual": 0,
|
232 |
+
"lambada_openai_mt_de": 0,
|
233 |
+
"lambada_openai_mt_en": 0,
|
234 |
+
"lambada_openai_mt_es": 0,
|
235 |
+
"lambada_openai_mt_fr": 0,
|
236 |
+
"lambada_openai_mt_it": 0
|
237 |
+
},
|
238 |
+
"config": {
|
239 |
+
"model": "hf",
|
240 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
241 |
+
"batch_size": "auto",
|
242 |
+
"batch_sizes": [
|
243 |
+
32
|
244 |
+
],
|
245 |
+
"device": null,
|
246 |
+
"use_cache": null,
|
247 |
+
"limit": null,
|
248 |
+
"bootstrap_iters": 100000,
|
249 |
+
"gen_kwargs": null
|
250 |
+
},
|
251 |
+
"git_hash": "9b1cd24"
|
252 |
+
}
|
lm-eval-output/huggyllama/llama-7b/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b57212ed1c8fe8ebcf0e72e4b4b7f53ccc5568de4d2dc00307b4357f22419de1
|
3 |
+
size 114496
|
lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e1c638a150077d635d91db5d86f0fddeb34a256051c1ac91bd5344a6590f69bb
|
3 |
+
size 2404891
|
lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,283 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"pawsx": {
|
4 |
+
"acc,none": 0.44671428571428573,
|
5 |
+
"acc_stderr,none": 0.05195047972137848,
|
6 |
+
"alias": "pawsx"
|
7 |
+
},
|
8 |
+
"paws_de": {
|
9 |
+
"acc,none": 0.4075,
|
10 |
+
"acc_stderr,none": 0.010990098549743105,
|
11 |
+
"alias": " - paws_de"
|
12 |
+
},
|
13 |
+
"paws_en": {
|
14 |
+
"acc,none": 0.3345,
|
15 |
+
"acc_stderr,none": 0.010552751076266157,
|
16 |
+
"alias": " - paws_en"
|
17 |
+
},
|
18 |
+
"paws_es": {
|
19 |
+
"acc,none": 0.398,
|
20 |
+
"acc_stderr,none": 0.010947964603728239,
|
21 |
+
"alias": " - paws_es"
|
22 |
+
},
|
23 |
+
"paws_fr": {
|
24 |
+
"acc,none": 0.517,
|
25 |
+
"acc_stderr,none": 0.01117667029931067,
|
26 |
+
"alias": " - paws_fr"
|
27 |
+
},
|
28 |
+
"paws_ja": {
|
29 |
+
"acc,none": 0.441,
|
30 |
+
"acc_stderr,none": 0.011105006104468736,
|
31 |
+
"alias": " - paws_ja"
|
32 |
+
},
|
33 |
+
"paws_ko": {
|
34 |
+
"acc,none": 0.5085,
|
35 |
+
"acc_stderr,none": 0.011181519941139164,
|
36 |
+
"alias": " - paws_ko"
|
37 |
+
},
|
38 |
+
"paws_zh": {
|
39 |
+
"acc,none": 0.5205,
|
40 |
+
"acc_stderr,none": 0.011173732641806813,
|
41 |
+
"alias": " - paws_zh"
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"groups": {
|
45 |
+
"pawsx": {
|
46 |
+
"acc,none": 0.44671428571428573,
|
47 |
+
"acc_stderr,none": 0.05195047972137848,
|
48 |
+
"alias": "pawsx"
|
49 |
+
}
|
50 |
+
},
|
51 |
+
"configs": {
|
52 |
+
"paws_de": {
|
53 |
+
"task": "paws_de",
|
54 |
+
"group": "pawsx",
|
55 |
+
"dataset_path": "paws-x",
|
56 |
+
"dataset_name": "de",
|
57 |
+
"training_split": "train",
|
58 |
+
"validation_split": "validation",
|
59 |
+
"test_split": "test",
|
60 |
+
"doc_to_text": "",
|
61 |
+
"doc_to_target": "label",
|
62 |
+
"doc_to_choice": "{{[sentence1+\", richtig? Ja, \"+sentence2, sentence1+\", richtig? Nein, \"+sentence2]}}",
|
63 |
+
"description": "",
|
64 |
+
"target_delimiter": " ",
|
65 |
+
"fewshot_delimiter": "\n\n",
|
66 |
+
"metric_list": [
|
67 |
+
{
|
68 |
+
"metric": "acc",
|
69 |
+
"aggregation": "mean",
|
70 |
+
"higher_is_better": true
|
71 |
+
}
|
72 |
+
],
|
73 |
+
"output_type": "multiple_choice",
|
74 |
+
"repeats": 1,
|
75 |
+
"should_decontaminate": false,
|
76 |
+
"metadata": {
|
77 |
+
"version": 0.0
|
78 |
+
}
|
79 |
+
},
|
80 |
+
"paws_en": {
|
81 |
+
"task": "paws_en",
|
82 |
+
"group": "pawsx",
|
83 |
+
"dataset_path": "paws-x",
|
84 |
+
"dataset_name": "en",
|
85 |
+
"training_split": "train",
|
86 |
+
"validation_split": "validation",
|
87 |
+
"test_split": "test",
|
88 |
+
"doc_to_text": "",
|
89 |
+
"doc_to_target": "label",
|
90 |
+
"doc_to_choice": "{{[sentence1+\", right? Yes, \"+sentence2, sentence1+\", right? No, \"+sentence2]}}",
|
91 |
+
"description": "",
|
92 |
+
"target_delimiter": " ",
|
93 |
+
"fewshot_delimiter": "\n\n",
|
94 |
+
"metric_list": [
|
95 |
+
{
|
96 |
+
"metric": "acc",
|
97 |
+
"aggregation": "mean",
|
98 |
+
"higher_is_better": true
|
99 |
+
}
|
100 |
+
],
|
101 |
+
"output_type": "multiple_choice",
|
102 |
+
"repeats": 1,
|
103 |
+
"should_decontaminate": false,
|
104 |
+
"metadata": {
|
105 |
+
"version": 0.0
|
106 |
+
}
|
107 |
+
},
|
108 |
+
"paws_es": {
|
109 |
+
"task": "paws_es",
|
110 |
+
"group": "pawsx",
|
111 |
+
"dataset_path": "paws-x",
|
112 |
+
"dataset_name": "es",
|
113 |
+
"training_split": "train",
|
114 |
+
"validation_split": "validation",
|
115 |
+
"test_split": "test",
|
116 |
+
"doc_to_text": "",
|
117 |
+
"doc_to_target": "label",
|
118 |
+
"doc_to_choice": "{{[sentence1+\", verdad? Sí, \"+sentence2, sentence1+\", verdad? No, \"+sentence2]}}",
|
119 |
+
"description": "",
|
120 |
+
"target_delimiter": " ",
|
121 |
+
"fewshot_delimiter": "\n\n",
|
122 |
+
"metric_list": [
|
123 |
+
{
|
124 |
+
"metric": "acc",
|
125 |
+
"aggregation": "mean",
|
126 |
+
"higher_is_better": true
|
127 |
+
}
|
128 |
+
],
|
129 |
+
"output_type": "multiple_choice",
|
130 |
+
"repeats": 1,
|
131 |
+
"should_decontaminate": false,
|
132 |
+
"metadata": {
|
133 |
+
"version": 0.0
|
134 |
+
}
|
135 |
+
},
|
136 |
+
"paws_fr": {
|
137 |
+
"task": "paws_fr",
|
138 |
+
"group": "pawsx",
|
139 |
+
"dataset_path": "paws-x",
|
140 |
+
"dataset_name": "fr",
|
141 |
+
"training_split": "train",
|
142 |
+
"validation_split": "validation",
|
143 |
+
"test_split": "test",
|
144 |
+
"doc_to_text": "",
|
145 |
+
"doc_to_target": "label",
|
146 |
+
"doc_to_choice": "{{[sentence1+\", n'est-ce pas? Oui, \"+sentence2, sentence1+\", n'est-ce pas? No, \"+sentence2]}}",
|
147 |
+
"description": "",
|
148 |
+
"target_delimiter": " ",
|
149 |
+
"fewshot_delimiter": "\n\n",
|
150 |
+
"metric_list": [
|
151 |
+
{
|
152 |
+
"metric": "acc",
|
153 |
+
"aggregation": "mean",
|
154 |
+
"higher_is_better": true
|
155 |
+
}
|
156 |
+
],
|
157 |
+
"output_type": "multiple_choice",
|
158 |
+
"repeats": 1,
|
159 |
+
"should_decontaminate": false,
|
160 |
+
"metadata": {
|
161 |
+
"version": 0.0
|
162 |
+
}
|
163 |
+
},
|
164 |
+
"paws_ja": {
|
165 |
+
"task": "paws_ja",
|
166 |
+
"group": "pawsx",
|
167 |
+
"dataset_path": "paws-x",
|
168 |
+
"dataset_name": "ja",
|
169 |
+
"training_split": "train",
|
170 |
+
"validation_split": "validation",
|
171 |
+
"test_split": "test",
|
172 |
+
"doc_to_text": "",
|
173 |
+
"doc_to_target": "label",
|
174 |
+
"doc_to_choice": "{{[sentence1+\", ですね? はい, \"+sentence2, sentence1+\", ですね? いいえ, \"+sentence2]}}",
|
175 |
+
"description": "",
|
176 |
+
"target_delimiter": " ",
|
177 |
+
"fewshot_delimiter": "\n\n",
|
178 |
+
"metric_list": [
|
179 |
+
{
|
180 |
+
"metric": "acc",
|
181 |
+
"aggregation": "mean",
|
182 |
+
"higher_is_better": true
|
183 |
+
}
|
184 |
+
],
|
185 |
+
"output_type": "multiple_choice",
|
186 |
+
"repeats": 1,
|
187 |
+
"should_decontaminate": false,
|
188 |
+
"metadata": {
|
189 |
+
"version": 0.0
|
190 |
+
}
|
191 |
+
},
|
192 |
+
"paws_ko": {
|
193 |
+
"task": "paws_ko",
|
194 |
+
"group": "pawsx",
|
195 |
+
"dataset_path": "paws-x",
|
196 |
+
"dataset_name": "ko",
|
197 |
+
"training_split": "train",
|
198 |
+
"validation_split": "validation",
|
199 |
+
"test_split": "test",
|
200 |
+
"doc_to_text": "",
|
201 |
+
"doc_to_target": "label",
|
202 |
+
"doc_to_choice": "{{[sentence1+\", 맞죠? 예, \"+sentence2, sentence1+\", 맞죠? 아니요, \"+sentence2]}}",
|
203 |
+
"description": "",
|
204 |
+
"target_delimiter": " ",
|
205 |
+
"fewshot_delimiter": "\n\n",
|
206 |
+
"metric_list": [
|
207 |
+
{
|
208 |
+
"metric": "acc",
|
209 |
+
"aggregation": "mean",
|
210 |
+
"higher_is_better": true
|
211 |
+
}
|
212 |
+
],
|
213 |
+
"output_type": "multiple_choice",
|
214 |
+
"repeats": 1,
|
215 |
+
"should_decontaminate": false,
|
216 |
+
"metadata": {
|
217 |
+
"version": 0.0
|
218 |
+
}
|
219 |
+
},
|
220 |
+
"paws_zh": {
|
221 |
+
"task": "paws_zh",
|
222 |
+
"group": "pawsx",
|
223 |
+
"dataset_path": "paws-x",
|
224 |
+
"dataset_name": "zh",
|
225 |
+
"training_split": "train",
|
226 |
+
"validation_split": "validation",
|
227 |
+
"test_split": "test",
|
228 |
+
"doc_to_text": "",
|
229 |
+
"doc_to_target": "label",
|
230 |
+
"doc_to_choice": "{{[sentence1+\", 对吧? 是, \"+sentence2, sentence1+\", 对吧? 不是, \"+sentence2]}}",
|
231 |
+
"description": "",
|
232 |
+
"target_delimiter": " ",
|
233 |
+
"fewshot_delimiter": "\n\n",
|
234 |
+
"metric_list": [
|
235 |
+
{
|
236 |
+
"metric": "acc",
|
237 |
+
"aggregation": "mean",
|
238 |
+
"higher_is_better": true
|
239 |
+
}
|
240 |
+
],
|
241 |
+
"output_type": "multiple_choice",
|
242 |
+
"repeats": 1,
|
243 |
+
"should_decontaminate": false,
|
244 |
+
"metadata": {
|
245 |
+
"version": 0.0
|
246 |
+
}
|
247 |
+
}
|
248 |
+
},
|
249 |
+
"versions": {
|
250 |
+
"paws_de": 0.0,
|
251 |
+
"paws_en": 0.0,
|
252 |
+
"paws_es": 0.0,
|
253 |
+
"paws_fr": 0.0,
|
254 |
+
"paws_ja": 0.0,
|
255 |
+
"paws_ko": 0.0,
|
256 |
+
"paws_zh": 0.0,
|
257 |
+
"pawsx": "N/A"
|
258 |
+
},
|
259 |
+
"n-shot": {
|
260 |
+
"paws_de": 0,
|
261 |
+
"paws_en": 0,
|
262 |
+
"paws_es": 0,
|
263 |
+
"paws_fr": 0,
|
264 |
+
"paws_ja": 0,
|
265 |
+
"paws_ko": 0,
|
266 |
+
"paws_zh": 0,
|
267 |
+
"pawsx": 0
|
268 |
+
},
|
269 |
+
"config": {
|
270 |
+
"model": "hf",
|
271 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
272 |
+
"batch_size": "auto",
|
273 |
+
"batch_sizes": [
|
274 |
+
16
|
275 |
+
],
|
276 |
+
"device": null,
|
277 |
+
"use_cache": null,
|
278 |
+
"limit": null,
|
279 |
+
"bootstrap_iters": 100000,
|
280 |
+
"gen_kwargs": null
|
281 |
+
},
|
282 |
+
"git_hash": "9b1cd24"
|
283 |
+
}
|
lm-eval-output/huggyllama/llama-7b/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:39c529453a270120fa274be1e00bbcc806a5652f93c1f758ca9b3b46294dcd12
|
3 |
+
size 80836
|
lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a39f959991979fb0c9072ba6cf5c9ddc23c706250118fbf8254693023ad6510e
|
3 |
+
size 643920
|
lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,390 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"xcopa": {
|
4 |
+
"acc,none": 0.5418181818181819,
|
5 |
+
"acc_stderr,none": 0.040717736708881784,
|
6 |
+
"alias": "xcopa"
|
7 |
+
},
|
8 |
+
"xcopa_et": {
|
9 |
+
"acc,none": 0.492,
|
10 |
+
"acc_stderr,none": 0.022380208834928028,
|
11 |
+
"alias": " - xcopa_et"
|
12 |
+
},
|
13 |
+
"xcopa_ht": {
|
14 |
+
"acc,none": 0.51,
|
15 |
+
"acc_stderr,none": 0.02237859698923078,
|
16 |
+
"alias": " - xcopa_ht"
|
17 |
+
},
|
18 |
+
"xcopa_id": {
|
19 |
+
"acc,none": 0.552,
|
20 |
+
"acc_stderr,none": 0.02226169729227013,
|
21 |
+
"alias": " - xcopa_id"
|
22 |
+
},
|
23 |
+
"xcopa_it": {
|
24 |
+
"acc,none": 0.646,
|
25 |
+
"acc_stderr,none": 0.02140758204791645,
|
26 |
+
"alias": " - xcopa_it"
|
27 |
+
},
|
28 |
+
"xcopa_qu": {
|
29 |
+
"acc,none": 0.518,
|
30 |
+
"acc_stderr,none": 0.02236856511738799,
|
31 |
+
"alias": " - xcopa_qu"
|
32 |
+
},
|
33 |
+
"xcopa_sw": {
|
34 |
+
"acc,none": 0.5,
|
35 |
+
"acc_stderr,none": 0.022383074051792257,
|
36 |
+
"alias": " - xcopa_sw"
|
37 |
+
},
|
38 |
+
"xcopa_ta": {
|
39 |
+
"acc,none": 0.544,
|
40 |
+
"acc_stderr,none": 0.02229623834840706,
|
41 |
+
"alias": " - xcopa_ta"
|
42 |
+
},
|
43 |
+
"xcopa_th": {
|
44 |
+
"acc,none": 0.558,
|
45 |
+
"acc_stderr,none": 0.02223197069632112,
|
46 |
+
"alias": " - xcopa_th"
|
47 |
+
},
|
48 |
+
"xcopa_tr": {
|
49 |
+
"acc,none": 0.556,
|
50 |
+
"acc_stderr,none": 0.02224224437573102,
|
51 |
+
"alias": " - xcopa_tr"
|
52 |
+
},
|
53 |
+
"xcopa_vi": {
|
54 |
+
"acc,none": 0.518,
|
55 |
+
"acc_stderr,none": 0.02236856511738799,
|
56 |
+
"alias": " - xcopa_vi"
|
57 |
+
},
|
58 |
+
"xcopa_zh": {
|
59 |
+
"acc,none": 0.566,
|
60 |
+
"acc_stderr,none": 0.02218721580302901,
|
61 |
+
"alias": " - xcopa_zh"
|
62 |
+
}
|
63 |
+
},
|
64 |
+
"groups": {
|
65 |
+
"xcopa": {
|
66 |
+
"acc,none": 0.5418181818181819,
|
67 |
+
"acc_stderr,none": 0.040717736708881784,
|
68 |
+
"alias": "xcopa"
|
69 |
+
}
|
70 |
+
},
|
71 |
+
"configs": {
|
72 |
+
"xcopa_et": {
|
73 |
+
"task": "xcopa_et",
|
74 |
+
"group": "xcopa",
|
75 |
+
"dataset_path": "xcopa",
|
76 |
+
"dataset_name": "et",
|
77 |
+
"validation_split": "validation",
|
78 |
+
"test_split": "test",
|
79 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b1f759e0>, connector={'cause': 'sest', 'effect': 'seetõttu'})",
|
80 |
+
"doc_to_target": "label",
|
81 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
82 |
+
"description": "",
|
83 |
+
"target_delimiter": " ",
|
84 |
+
"fewshot_delimiter": "\n\n",
|
85 |
+
"metric_list": [
|
86 |
+
{
|
87 |
+
"metric": "acc"
|
88 |
+
}
|
89 |
+
],
|
90 |
+
"output_type": "multiple_choice",
|
91 |
+
"repeats": 1,
|
92 |
+
"should_decontaminate": false,
|
93 |
+
"metadata": {
|
94 |
+
"version": 1.0
|
95 |
+
}
|
96 |
+
},
|
97 |
+
"xcopa_ht": {
|
98 |
+
"task": "xcopa_ht",
|
99 |
+
"group": "xcopa",
|
100 |
+
"dataset_path": "xcopa",
|
101 |
+
"dataset_name": "ht",
|
102 |
+
"validation_split": "validation",
|
103 |
+
"test_split": "test",
|
104 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80dd300>, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
|
105 |
+
"doc_to_target": "label",
|
106 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
107 |
+
"description": "",
|
108 |
+
"target_delimiter": " ",
|
109 |
+
"fewshot_delimiter": "\n\n",
|
110 |
+
"metric_list": [
|
111 |
+
{
|
112 |
+
"metric": "acc"
|
113 |
+
}
|
114 |
+
],
|
115 |
+
"output_type": "multiple_choice",
|
116 |
+
"repeats": 1,
|
117 |
+
"should_decontaminate": false,
|
118 |
+
"metadata": {
|
119 |
+
"version": 1.0
|
120 |
+
}
|
121 |
+
},
|
122 |
+
"xcopa_id": {
|
123 |
+
"task": "xcopa_id",
|
124 |
+
"group": "xcopa",
|
125 |
+
"dataset_path": "xcopa",
|
126 |
+
"dataset_name": "id",
|
127 |
+
"validation_split": "validation",
|
128 |
+
"test_split": "test",
|
129 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b1f740e0>, connector={'cause': 'karena', 'effect': 'maka'})",
|
130 |
+
"doc_to_target": "label",
|
131 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
132 |
+
"description": "",
|
133 |
+
"target_delimiter": " ",
|
134 |
+
"fewshot_delimiter": "\n\n",
|
135 |
+
"metric_list": [
|
136 |
+
{
|
137 |
+
"metric": "acc"
|
138 |
+
}
|
139 |
+
],
|
140 |
+
"output_type": "multiple_choice",
|
141 |
+
"repeats": 1,
|
142 |
+
"should_decontaminate": false,
|
143 |
+
"metadata": {
|
144 |
+
"version": 1.0
|
145 |
+
}
|
146 |
+
},
|
147 |
+
"xcopa_it": {
|
148 |
+
"task": "xcopa_it",
|
149 |
+
"group": "xcopa",
|
150 |
+
"dataset_path": "xcopa",
|
151 |
+
"dataset_name": "it",
|
152 |
+
"validation_split": "validation",
|
153 |
+
"test_split": "test",
|
154 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80dc180>, connector={'cause': 'perché', 'effect': 'quindi'})",
|
155 |
+
"doc_to_target": "label",
|
156 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
157 |
+
"description": "",
|
158 |
+
"target_delimiter": " ",
|
159 |
+
"fewshot_delimiter": "\n\n",
|
160 |
+
"metric_list": [
|
161 |
+
{
|
162 |
+
"metric": "acc"
|
163 |
+
}
|
164 |
+
],
|
165 |
+
"output_type": "multiple_choice",
|
166 |
+
"repeats": 1,
|
167 |
+
"should_decontaminate": false,
|
168 |
+
"metadata": {
|
169 |
+
"version": 1.0
|
170 |
+
}
|
171 |
+
},
|
172 |
+
"xcopa_qu": {
|
173 |
+
"task": "xcopa_qu",
|
174 |
+
"group": "xcopa",
|
175 |
+
"dataset_path": "xcopa",
|
176 |
+
"dataset_name": "qu",
|
177 |
+
"validation_split": "validation",
|
178 |
+
"test_split": "test",
|
179 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97ba65e340>, connector={'cause': 'imataq', 'effect': 'chaymi'})",
|
180 |
+
"doc_to_target": "label",
|
181 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
182 |
+
"description": "",
|
183 |
+
"target_delimiter": " ",
|
184 |
+
"fewshot_delimiter": "\n\n",
|
185 |
+
"metric_list": [
|
186 |
+
{
|
187 |
+
"metric": "acc"
|
188 |
+
}
|
189 |
+
],
|
190 |
+
"output_type": "multiple_choice",
|
191 |
+
"repeats": 1,
|
192 |
+
"should_decontaminate": false,
|
193 |
+
"metadata": {
|
194 |
+
"version": 1.0
|
195 |
+
}
|
196 |
+
},
|
197 |
+
"xcopa_sw": {
|
198 |
+
"task": "xcopa_sw",
|
199 |
+
"group": "xcopa",
|
200 |
+
"dataset_path": "xcopa",
|
201 |
+
"dataset_name": "sw",
|
202 |
+
"validation_split": "validation",
|
203 |
+
"test_split": "test",
|
204 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80dc0e0>, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
|
205 |
+
"doc_to_target": "label",
|
206 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
207 |
+
"description": "",
|
208 |
+
"target_delimiter": " ",
|
209 |
+
"fewshot_delimiter": "\n\n",
|
210 |
+
"metric_list": [
|
211 |
+
{
|
212 |
+
"metric": "acc"
|
213 |
+
}
|
214 |
+
],
|
215 |
+
"output_type": "multiple_choice",
|
216 |
+
"repeats": 1,
|
217 |
+
"should_decontaminate": false,
|
218 |
+
"metadata": {
|
219 |
+
"version": 1.0
|
220 |
+
}
|
221 |
+
},
|
222 |
+
"xcopa_ta": {
|
223 |
+
"task": "xcopa_ta",
|
224 |
+
"group": "xcopa",
|
225 |
+
"dataset_path": "xcopa",
|
226 |
+
"dataset_name": "ta",
|
227 |
+
"validation_split": "validation",
|
228 |
+
"test_split": "test",
|
229 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80de480>, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
|
230 |
+
"doc_to_target": "label",
|
231 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
232 |
+
"description": "",
|
233 |
+
"target_delimiter": " ",
|
234 |
+
"fewshot_delimiter": "\n\n",
|
235 |
+
"metric_list": [
|
236 |
+
{
|
237 |
+
"metric": "acc"
|
238 |
+
}
|
239 |
+
],
|
240 |
+
"output_type": "multiple_choice",
|
241 |
+
"repeats": 1,
|
242 |
+
"should_decontaminate": false,
|
243 |
+
"metadata": {
|
244 |
+
"version": 1.0
|
245 |
+
}
|
246 |
+
},
|
247 |
+
"xcopa_th": {
|
248 |
+
"task": "xcopa_th",
|
249 |
+
"group": "xcopa",
|
250 |
+
"dataset_path": "xcopa",
|
251 |
+
"dataset_name": "th",
|
252 |
+
"validation_split": "validation",
|
253 |
+
"test_split": "test",
|
254 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80932e0>, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
|
255 |
+
"doc_to_target": "label",
|
256 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
257 |
+
"description": "",
|
258 |
+
"target_delimiter": " ",
|
259 |
+
"fewshot_delimiter": "\n\n",
|
260 |
+
"metric_list": [
|
261 |
+
{
|
262 |
+
"metric": "acc"
|
263 |
+
}
|
264 |
+
],
|
265 |
+
"output_type": "multiple_choice",
|
266 |
+
"repeats": 1,
|
267 |
+
"should_decontaminate": false,
|
268 |
+
"metadata": {
|
269 |
+
"version": 1.0
|
270 |
+
}
|
271 |
+
},
|
272 |
+
"xcopa_tr": {
|
273 |
+
"task": "xcopa_tr",
|
274 |
+
"group": "xcopa",
|
275 |
+
"dataset_path": "xcopa",
|
276 |
+
"dataset_name": "tr",
|
277 |
+
"validation_split": "validation",
|
278 |
+
"test_split": "test",
|
279 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b80562a0>, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
|
280 |
+
"doc_to_target": "label",
|
281 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
282 |
+
"description": "",
|
283 |
+
"target_delimiter": " ",
|
284 |
+
"fewshot_delimiter": "\n\n",
|
285 |
+
"metric_list": [
|
286 |
+
{
|
287 |
+
"metric": "acc"
|
288 |
+
}
|
289 |
+
],
|
290 |
+
"output_type": "multiple_choice",
|
291 |
+
"repeats": 1,
|
292 |
+
"should_decontaminate": false,
|
293 |
+
"metadata": {
|
294 |
+
"version": 1.0
|
295 |
+
}
|
296 |
+
},
|
297 |
+
"xcopa_vi": {
|
298 |
+
"task": "xcopa_vi",
|
299 |
+
"group": "xcopa",
|
300 |
+
"dataset_path": "xcopa",
|
301 |
+
"dataset_name": "vi",
|
302 |
+
"validation_split": "validation",
|
303 |
+
"test_split": "test",
|
304 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97b8090900>, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
|
305 |
+
"doc_to_target": "label",
|
306 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
307 |
+
"description": "",
|
308 |
+
"target_delimiter": " ",
|
309 |
+
"fewshot_delimiter": "\n\n",
|
310 |
+
"metric_list": [
|
311 |
+
{
|
312 |
+
"metric": "acc"
|
313 |
+
}
|
314 |
+
],
|
315 |
+
"output_type": "multiple_choice",
|
316 |
+
"repeats": 1,
|
317 |
+
"should_decontaminate": false,
|
318 |
+
"metadata": {
|
319 |
+
"version": 1.0
|
320 |
+
}
|
321 |
+
},
|
322 |
+
"xcopa_zh": {
|
323 |
+
"task": "xcopa_zh",
|
324 |
+
"group": "xcopa",
|
325 |
+
"dataset_path": "xcopa",
|
326 |
+
"dataset_name": "zh",
|
327 |
+
"validation_split": "validation",
|
328 |
+
"test_split": "test",
|
329 |
+
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f97ba65d800>, connector={'cause': '因为', 'effect': '所以'})",
|
330 |
+
"doc_to_target": "label",
|
331 |
+
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
332 |
+
"description": "",
|
333 |
+
"target_delimiter": " ",
|
334 |
+
"fewshot_delimiter": "\n\n",
|
335 |
+
"metric_list": [
|
336 |
+
{
|
337 |
+
"metric": "acc"
|
338 |
+
}
|
339 |
+
],
|
340 |
+
"output_type": "multiple_choice",
|
341 |
+
"repeats": 1,
|
342 |
+
"should_decontaminate": false,
|
343 |
+
"metadata": {
|
344 |
+
"version": 1.0
|
345 |
+
}
|
346 |
+
}
|
347 |
+
},
|
348 |
+
"versions": {
|
349 |
+
"xcopa": "N/A",
|
350 |
+
"xcopa_et": 1.0,
|
351 |
+
"xcopa_ht": 1.0,
|
352 |
+
"xcopa_id": 1.0,
|
353 |
+
"xcopa_it": 1.0,
|
354 |
+
"xcopa_qu": 1.0,
|
355 |
+
"xcopa_sw": 1.0,
|
356 |
+
"xcopa_ta": 1.0,
|
357 |
+
"xcopa_th": 1.0,
|
358 |
+
"xcopa_tr": 1.0,
|
359 |
+
"xcopa_vi": 1.0,
|
360 |
+
"xcopa_zh": 1.0
|
361 |
+
},
|
362 |
+
"n-shot": {
|
363 |
+
"xcopa": 0,
|
364 |
+
"xcopa_et": 0,
|
365 |
+
"xcopa_ht": 0,
|
366 |
+
"xcopa_id": 0,
|
367 |
+
"xcopa_it": 0,
|
368 |
+
"xcopa_qu": 0,
|
369 |
+
"xcopa_sw": 0,
|
370 |
+
"xcopa_ta": 0,
|
371 |
+
"xcopa_th": 0,
|
372 |
+
"xcopa_tr": 0,
|
373 |
+
"xcopa_vi": 0,
|
374 |
+
"xcopa_zh": 0
|
375 |
+
},
|
376 |
+
"config": {
|
377 |
+
"model": "hf",
|
378 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
379 |
+
"batch_size": "auto",
|
380 |
+
"batch_sizes": [
|
381 |
+
32
|
382 |
+
],
|
383 |
+
"device": null,
|
384 |
+
"use_cache": null,
|
385 |
+
"limit": null,
|
386 |
+
"bootstrap_iters": 100000,
|
387 |
+
"gen_kwargs": null
|
388 |
+
},
|
389 |
+
"git_hash": "9b1cd24"
|
390 |
+
}
|
lm-eval-output/huggyllama/llama-7b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ab1eabeb856196d8e50313c8ceb1b6965bce88355d71e7f9c28cc52b0dda4cb9
|
3 |
+
size 96756
|
lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f56265d76e97b401029f3f26aad99b156400be6a7a0e0f76f4cb98842139d4a6
|
3 |
+
size 7098708
|
lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,548 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"xnli": {
|
4 |
+
"acc,none": 0.38867469879518074,
|
5 |
+
"acc_stderr,none": 0.05695391505524146,
|
6 |
+
"alias": "xnli"
|
7 |
+
},
|
8 |
+
"xnli_ar": {
|
9 |
+
"acc,none": 0.3397590361445783,
|
10 |
+
"acc_stderr,none": 0.009493454925438252,
|
11 |
+
"alias": " - xnli_ar"
|
12 |
+
},
|
13 |
+
"xnli_bg": {
|
14 |
+
"acc,none": 0.38032128514056224,
|
15 |
+
"acc_stderr,none": 0.009730746464767608,
|
16 |
+
"alias": " - xnli_bg"
|
17 |
+
},
|
18 |
+
"xnli_de": {
|
19 |
+
"acc,none": 0.463855421686747,
|
20 |
+
"acc_stderr,none": 0.00999585228282238,
|
21 |
+
"alias": " - xnli_de"
|
22 |
+
},
|
23 |
+
"xnli_el": {
|
24 |
+
"acc,none": 0.3389558232931727,
|
25 |
+
"acc_stderr,none": 0.009487992732201524,
|
26 |
+
"alias": " - xnli_el"
|
27 |
+
},
|
28 |
+
"xnli_en": {
|
29 |
+
"acc,none": 0.5389558232931727,
|
30 |
+
"acc_stderr,none": 0.009991608448389058,
|
31 |
+
"alias": " - xnli_en"
|
32 |
+
},
|
33 |
+
"xnli_es": {
|
34 |
+
"acc,none": 0.43253012048192774,
|
35 |
+
"acc_stderr,none": 0.009930409027139452,
|
36 |
+
"alias": " - xnli_es"
|
37 |
+
},
|
38 |
+
"xnli_fr": {
|
39 |
+
"acc,none": 0.4779116465863454,
|
40 |
+
"acc_stderr,none": 0.010012288645591786,
|
41 |
+
"alias": " - xnli_fr"
|
42 |
+
},
|
43 |
+
"xnli_hi": {
|
44 |
+
"acc,none": 0.3493975903614458,
|
45 |
+
"acc_stderr,none": 0.009556642460138152,
|
46 |
+
"alias": " - xnli_hi"
|
47 |
+
},
|
48 |
+
"xnli_ru": {
|
49 |
+
"acc,none": 0.4389558232931727,
|
50 |
+
"acc_stderr,none": 0.009947100105978365,
|
51 |
+
"alias": " - xnli_ru"
|
52 |
+
},
|
53 |
+
"xnli_sw": {
|
54 |
+
"acc,none": 0.3365461847389558,
|
55 |
+
"acc_stderr,none": 0.009471423054177119,
|
56 |
+
"alias": " - xnli_sw"
|
57 |
+
},
|
58 |
+
"xnli_th": {
|
59 |
+
"acc,none": 0.3192771084337349,
|
60 |
+
"acc_stderr,none": 0.009344511873557408,
|
61 |
+
"alias": " - xnli_th"
|
62 |
+
},
|
63 |
+
"xnli_tr": {
|
64 |
+
"acc,none": 0.3506024096385542,
|
65 |
+
"acc_stderr,none": 0.009564237156206103,
|
66 |
+
"alias": " - xnli_tr"
|
67 |
+
},
|
68 |
+
"xnli_ur": {
|
69 |
+
"acc,none": 0.3373493975903614,
|
70 |
+
"acc_stderr,none": 0.009476976849778591,
|
71 |
+
"alias": " - xnli_ur"
|
72 |
+
},
|
73 |
+
"xnli_vi": {
|
74 |
+
"acc,none": 0.37710843373493974,
|
75 |
+
"acc_stderr,none": 0.009714644211180594,
|
76 |
+
"alias": " - xnli_vi"
|
77 |
+
},
|
78 |
+
"xnli_zh": {
|
79 |
+
"acc,none": 0.3485943775100402,
|
80 |
+
"acc_stderr,none": 0.009551542053301817,
|
81 |
+
"alias": " - xnli_zh"
|
82 |
+
}
|
83 |
+
},
|
84 |
+
"groups": {
|
85 |
+
"xnli": {
|
86 |
+
"acc,none": 0.38867469879518074,
|
87 |
+
"acc_stderr,none": 0.05695391505524146,
|
88 |
+
"alias": "xnli"
|
89 |
+
}
|
90 |
+
},
|
91 |
+
"configs": {
|
92 |
+
"xnli_ar": {
|
93 |
+
"task": "xnli_ar",
|
94 |
+
"group": "xnli",
|
95 |
+
"dataset_path": "xnli",
|
96 |
+
"dataset_name": "ar",
|
97 |
+
"training_split": "train",
|
98 |
+
"validation_split": "validation",
|
99 |
+
"doc_to_text": "",
|
100 |
+
"doc_to_target": "label",
|
101 |
+
"doc_to_choice": "{{[premise+\", صحيح? نعم, \"+hypothesis,premise+\", صحيح? لذا, \"+hypothesis,premise+\", صحيح? رقم, \"+hypothesis]}}",
|
102 |
+
"description": "",
|
103 |
+
"target_delimiter": " ",
|
104 |
+
"fewshot_delimiter": "\n\n",
|
105 |
+
"metric_list": [
|
106 |
+
{
|
107 |
+
"metric": "acc",
|
108 |
+
"aggregation": "mean",
|
109 |
+
"higher_is_better": true
|
110 |
+
}
|
111 |
+
],
|
112 |
+
"output_type": "multiple_choice",
|
113 |
+
"repeats": 1,
|
114 |
+
"should_decontaminate": false,
|
115 |
+
"metadata": {
|
116 |
+
"version": 1.0
|
117 |
+
}
|
118 |
+
},
|
119 |
+
"xnli_bg": {
|
120 |
+
"task": "xnli_bg",
|
121 |
+
"group": "xnli",
|
122 |
+
"dataset_path": "xnli",
|
123 |
+
"dataset_name": "bg",
|
124 |
+
"training_split": "train",
|
125 |
+
"validation_split": "validation",
|
126 |
+
"doc_to_text": "",
|
127 |
+
"doc_to_target": "label",
|
128 |
+
"doc_to_choice": "{{[premise+\", правилно? да, \"+hypothesis,premise+\", правилно? така, \"+hypothesis,premise+\", правилно? не, \"+hypothesis]}}",
|
129 |
+
"description": "",
|
130 |
+
"target_delimiter": " ",
|
131 |
+
"fewshot_delimiter": "\n\n",
|
132 |
+
"metric_list": [
|
133 |
+
{
|
134 |
+
"metric": "acc",
|
135 |
+
"aggregation": "mean",
|
136 |
+
"higher_is_better": true
|
137 |
+
}
|
138 |
+
],
|
139 |
+
"output_type": "multiple_choice",
|
140 |
+
"repeats": 1,
|
141 |
+
"should_decontaminate": false,
|
142 |
+
"metadata": {
|
143 |
+
"version": 1.0
|
144 |
+
}
|
145 |
+
},
|
146 |
+
"xnli_de": {
|
147 |
+
"task": "xnli_de",
|
148 |
+
"group": "xnli",
|
149 |
+
"dataset_path": "xnli",
|
150 |
+
"dataset_name": "de",
|
151 |
+
"training_split": "train",
|
152 |
+
"validation_split": "validation",
|
153 |
+
"doc_to_text": "",
|
154 |
+
"doc_to_target": "label",
|
155 |
+
"doc_to_choice": "{{[premise+\", richtig? Ja, \"+hypothesis,premise+\", richtig? Auch, \"+hypothesis,premise+\", richtig? Nein, \"+hypothesis]}}",
|
156 |
+
"description": "",
|
157 |
+
"target_delimiter": " ",
|
158 |
+
"fewshot_delimiter": "\n\n",
|
159 |
+
"metric_list": [
|
160 |
+
{
|
161 |
+
"metric": "acc",
|
162 |
+
"aggregation": "mean",
|
163 |
+
"higher_is_better": true
|
164 |
+
}
|
165 |
+
],
|
166 |
+
"output_type": "multiple_choice",
|
167 |
+
"repeats": 1,
|
168 |
+
"should_decontaminate": false,
|
169 |
+
"metadata": {
|
170 |
+
"version": 1.0
|
171 |
+
}
|
172 |
+
},
|
173 |
+
"xnli_el": {
|
174 |
+
"task": "xnli_el",
|
175 |
+
"group": "xnli",
|
176 |
+
"dataset_path": "xnli",
|
177 |
+
"dataset_name": "el",
|
178 |
+
"training_split": "train",
|
179 |
+
"validation_split": "validation",
|
180 |
+
"doc_to_text": "",
|
181 |
+
"doc_to_target": "label",
|
182 |
+
"doc_to_choice": "{{[premise+\", σωστός? Ναί, \"+hypothesis,premise+\", σωστός? Έτσι, \"+hypothesis,premise+\", σωστός? όχι, \"+hypothesis]}}",
|
183 |
+
"description": "",
|
184 |
+
"target_delimiter": " ",
|
185 |
+
"fewshot_delimiter": "\n\n",
|
186 |
+
"metric_list": [
|
187 |
+
{
|
188 |
+
"metric": "acc",
|
189 |
+
"aggregation": "mean",
|
190 |
+
"higher_is_better": true
|
191 |
+
}
|
192 |
+
],
|
193 |
+
"output_type": "multiple_choice",
|
194 |
+
"repeats": 1,
|
195 |
+
"should_decontaminate": false,
|
196 |
+
"metadata": {
|
197 |
+
"version": 1.0
|
198 |
+
}
|
199 |
+
},
|
200 |
+
"xnli_en": {
|
201 |
+
"task": "xnli_en",
|
202 |
+
"group": "xnli",
|
203 |
+
"dataset_path": "xnli",
|
204 |
+
"dataset_name": "en",
|
205 |
+
"training_split": "train",
|
206 |
+
"validation_split": "validation",
|
207 |
+
"doc_to_text": "",
|
208 |
+
"doc_to_target": "label",
|
209 |
+
"doc_to_choice": "{{[premise+\", right? Yes, \"+hypothesis,premise+\", right? Also, \"+hypothesis,premise+\", right? No, \"+hypothesis]}}",
|
210 |
+
"description": "",
|
211 |
+
"target_delimiter": " ",
|
212 |
+
"fewshot_delimiter": "\n\n",
|
213 |
+
"metric_list": [
|
214 |
+
{
|
215 |
+
"metric": "acc",
|
216 |
+
"aggregation": "mean",
|
217 |
+
"higher_is_better": true
|
218 |
+
}
|
219 |
+
],
|
220 |
+
"output_type": "multiple_choice",
|
221 |
+
"repeats": 1,
|
222 |
+
"should_decontaminate": false,
|
223 |
+
"metadata": {
|
224 |
+
"version": 1.0
|
225 |
+
}
|
226 |
+
},
|
227 |
+
"xnli_es": {
|
228 |
+
"task": "xnli_es",
|
229 |
+
"group": "xnli",
|
230 |
+
"dataset_path": "xnli",
|
231 |
+
"dataset_name": "es",
|
232 |
+
"training_split": "train",
|
233 |
+
"validation_split": "validation",
|
234 |
+
"doc_to_text": "",
|
235 |
+
"doc_to_target": "label",
|
236 |
+
"doc_to_choice": "{{[premise+\", correcto? Sí, \"+hypothesis,premise+\", correcto? Asi que, \"+hypothesis,premise+\", correcto? No, \"+hypothesis]}}",
|
237 |
+
"description": "",
|
238 |
+
"target_delimiter": " ",
|
239 |
+
"fewshot_delimiter": "\n\n",
|
240 |
+
"metric_list": [
|
241 |
+
{
|
242 |
+
"metric": "acc",
|
243 |
+
"aggregation": "mean",
|
244 |
+
"higher_is_better": true
|
245 |
+
}
|
246 |
+
],
|
247 |
+
"output_type": "multiple_choice",
|
248 |
+
"repeats": 1,
|
249 |
+
"should_decontaminate": false,
|
250 |
+
"metadata": {
|
251 |
+
"version": 1.0
|
252 |
+
}
|
253 |
+
},
|
254 |
+
"xnli_fr": {
|
255 |
+
"task": "xnli_fr",
|
256 |
+
"group": "xnli",
|
257 |
+
"dataset_path": "xnli",
|
258 |
+
"dataset_name": "fr",
|
259 |
+
"training_split": "train",
|
260 |
+
"validation_split": "validation",
|
261 |
+
"doc_to_text": "",
|
262 |
+
"doc_to_target": "label",
|
263 |
+
"doc_to_choice": "{{[premise+\", correct? Oui, \"+hypothesis,premise+\", correct? Aussi, \"+hypothesis,premise+\", correct? Non, \"+hypothesis]}}",
|
264 |
+
"description": "",
|
265 |
+
"target_delimiter": " ",
|
266 |
+
"fewshot_delimiter": "\n\n",
|
267 |
+
"metric_list": [
|
268 |
+
{
|
269 |
+
"metric": "acc",
|
270 |
+
"aggregation": "mean",
|
271 |
+
"higher_is_better": true
|
272 |
+
}
|
273 |
+
],
|
274 |
+
"output_type": "multiple_choice",
|
275 |
+
"repeats": 1,
|
276 |
+
"should_decontaminate": false,
|
277 |
+
"metadata": {
|
278 |
+
"version": 1.0
|
279 |
+
}
|
280 |
+
},
|
281 |
+
"xnli_hi": {
|
282 |
+
"task": "xnli_hi",
|
283 |
+
"group": "xnli",
|
284 |
+
"dataset_path": "xnli",
|
285 |
+
"dataset_name": "hi",
|
286 |
+
"training_split": "train",
|
287 |
+
"validation_split": "validation",
|
288 |
+
"doc_to_text": "",
|
289 |
+
"doc_to_target": "label",
|
290 |
+
"doc_to_choice": "{{[premise+\", सही? हाँ, \"+hypothesis,premise+\", सही? इसलिए, \"+hypothesis,premise+\", सही? नहीं, \"+hypothesis]}}",
|
291 |
+
"description": "",
|
292 |
+
"target_delimiter": " ",
|
293 |
+
"fewshot_delimiter": "\n\n",
|
294 |
+
"metric_list": [
|
295 |
+
{
|
296 |
+
"metric": "acc",
|
297 |
+
"aggregation": "mean",
|
298 |
+
"higher_is_better": true
|
299 |
+
}
|
300 |
+
],
|
301 |
+
"output_type": "multiple_choice",
|
302 |
+
"repeats": 1,
|
303 |
+
"should_decontaminate": false,
|
304 |
+
"metadata": {
|
305 |
+
"version": 1.0
|
306 |
+
}
|
307 |
+
},
|
308 |
+
"xnli_ru": {
|
309 |
+
"task": "xnli_ru",
|
310 |
+
"group": "xnli",
|
311 |
+
"dataset_path": "xnli",
|
312 |
+
"dataset_name": "ru",
|
313 |
+
"training_split": "train",
|
314 |
+
"validation_split": "validation",
|
315 |
+
"doc_to_text": "",
|
316 |
+
"doc_to_target": "label",
|
317 |
+
"doc_to_choice": "{{[premise+\", правильно? Да, \"+hypothesis,premise+\", правильно? Так, \"+hypothesis,premise+\", правильно? Нет, \"+hypothesis]}}",
|
318 |
+
"description": "",
|
319 |
+
"target_delimiter": " ",
|
320 |
+
"fewshot_delimiter": "\n\n",
|
321 |
+
"metric_list": [
|
322 |
+
{
|
323 |
+
"metric": "acc",
|
324 |
+
"aggregation": "mean",
|
325 |
+
"higher_is_better": true
|
326 |
+
}
|
327 |
+
],
|
328 |
+
"output_type": "multiple_choice",
|
329 |
+
"repeats": 1,
|
330 |
+
"should_decontaminate": false,
|
331 |
+
"metadata": {
|
332 |
+
"version": 1.0
|
333 |
+
}
|
334 |
+
},
|
335 |
+
"xnli_sw": {
|
336 |
+
"task": "xnli_sw",
|
337 |
+
"group": "xnli",
|
338 |
+
"dataset_path": "xnli",
|
339 |
+
"dataset_name": "sw",
|
340 |
+
"training_split": "train",
|
341 |
+
"validation_split": "validation",
|
342 |
+
"doc_to_text": "",
|
343 |
+
"doc_to_target": "label",
|
344 |
+
"doc_to_choice": "{{[premise+\", sahihi? Ndiyo, \"+hypothesis,premise+\", sahihi? Hivyo, \"+hypothesis,premise+\", sahihi? Hapana, \"+hypothesis]}}",
|
345 |
+
"description": "",
|
346 |
+
"target_delimiter": " ",
|
347 |
+
"fewshot_delimiter": "\n\n",
|
348 |
+
"metric_list": [
|
349 |
+
{
|
350 |
+
"metric": "acc",
|
351 |
+
"aggregation": "mean",
|
352 |
+
"higher_is_better": true
|
353 |
+
}
|
354 |
+
],
|
355 |
+
"output_type": "multiple_choice",
|
356 |
+
"repeats": 1,
|
357 |
+
"should_decontaminate": false,
|
358 |
+
"metadata": {
|
359 |
+
"version": 1.0
|
360 |
+
}
|
361 |
+
},
|
362 |
+
"xnli_th": {
|
363 |
+
"task": "xnli_th",
|
364 |
+
"group": "xnli",
|
365 |
+
"dataset_path": "xnli",
|
366 |
+
"dataset_name": "th",
|
367 |
+
"training_split": "train",
|
368 |
+
"validation_split": "validation",
|
369 |
+
"doc_to_text": "",
|
370 |
+
"doc_to_target": "label",
|
371 |
+
"doc_to_choice": "{{[premise+\", ถูกต้อง? ใช่, \"+hypothesis,premise+\", ถูกต้อง? ดังนั้น, \"+hypothesis,premise+\", ถูกต้อง? ไม่, \"+hypothesis]}}",
|
372 |
+
"description": "",
|
373 |
+
"target_delimiter": " ",
|
374 |
+
"fewshot_delimiter": "\n\n",
|
375 |
+
"metric_list": [
|
376 |
+
{
|
377 |
+
"metric": "acc",
|
378 |
+
"aggregation": "mean",
|
379 |
+
"higher_is_better": true
|
380 |
+
}
|
381 |
+
],
|
382 |
+
"output_type": "multiple_choice",
|
383 |
+
"repeats": 1,
|
384 |
+
"should_decontaminate": false,
|
385 |
+
"metadata": {
|
386 |
+
"version": 1.0
|
387 |
+
}
|
388 |
+
},
|
389 |
+
"xnli_tr": {
|
390 |
+
"task": "xnli_tr",
|
391 |
+
"group": "xnli",
|
392 |
+
"dataset_path": "xnli",
|
393 |
+
"dataset_name": "tr",
|
394 |
+
"training_split": "train",
|
395 |
+
"validation_split": "validation",
|
396 |
+
"doc_to_text": "",
|
397 |
+
"doc_to_target": "label",
|
398 |
+
"doc_to_choice": "{{[premise+\", doğru? Evet, \"+hypothesis,premise+\", doğru? Böylece, \"+hypothesis,premise+\", doğru? Hayır, \"+hypothesis]}}",
|
399 |
+
"description": "",
|
400 |
+
"target_delimiter": " ",
|
401 |
+
"fewshot_delimiter": "\n\n",
|
402 |
+
"metric_list": [
|
403 |
+
{
|
404 |
+
"metric": "acc",
|
405 |
+
"aggregation": "mean",
|
406 |
+
"higher_is_better": true
|
407 |
+
}
|
408 |
+
],
|
409 |
+
"output_type": "multiple_choice",
|
410 |
+
"repeats": 1,
|
411 |
+
"should_decontaminate": false,
|
412 |
+
"metadata": {
|
413 |
+
"version": 1.0
|
414 |
+
}
|
415 |
+
},
|
416 |
+
"xnli_ur": {
|
417 |
+
"task": "xnli_ur",
|
418 |
+
"group": "xnli",
|
419 |
+
"dataset_path": "xnli",
|
420 |
+
"dataset_name": "ur",
|
421 |
+
"training_split": "train",
|
422 |
+
"validation_split": "validation",
|
423 |
+
"doc_to_text": "",
|
424 |
+
"doc_to_target": "label",
|
425 |
+
"doc_to_choice": "{{[premise+\", صحیح? جی ہاں, \"+hypothesis,premise+\", صحیح? اس لئے, \"+hypothesis,premise+\", صحیح? نہیں, \"+hypothesis]}}",
|
426 |
+
"description": "",
|
427 |
+
"target_delimiter": " ",
|
428 |
+
"fewshot_delimiter": "\n\n",
|
429 |
+
"metric_list": [
|
430 |
+
{
|
431 |
+
"metric": "acc",
|
432 |
+
"aggregation": "mean",
|
433 |
+
"higher_is_better": true
|
434 |
+
}
|
435 |
+
],
|
436 |
+
"output_type": "multiple_choice",
|
437 |
+
"repeats": 1,
|
438 |
+
"should_decontaminate": false,
|
439 |
+
"metadata": {
|
440 |
+
"version": 1.0
|
441 |
+
}
|
442 |
+
},
|
443 |
+
"xnli_vi": {
|
444 |
+
"task": "xnli_vi",
|
445 |
+
"group": "xnli",
|
446 |
+
"dataset_path": "xnli",
|
447 |
+
"dataset_name": "vi",
|
448 |
+
"training_split": "train",
|
449 |
+
"validation_split": "validation",
|
450 |
+
"doc_to_text": "",
|
451 |
+
"doc_to_target": "label",
|
452 |
+
"doc_to_choice": "{{[premise+\", đúng? Vâng, \"+hypothesis,premise+\", đúng? Vì vậy, \"+hypothesis,premise+\", đúng? Không, \"+hypothesis]}}",
|
453 |
+
"description": "",
|
454 |
+
"target_delimiter": " ",
|
455 |
+
"fewshot_delimiter": "\n\n",
|
456 |
+
"metric_list": [
|
457 |
+
{
|
458 |
+
"metric": "acc",
|
459 |
+
"aggregation": "mean",
|
460 |
+
"higher_is_better": true
|
461 |
+
}
|
462 |
+
],
|
463 |
+
"output_type": "multiple_choice",
|
464 |
+
"repeats": 1,
|
465 |
+
"should_decontaminate": false,
|
466 |
+
"metadata": {
|
467 |
+
"version": 1.0
|
468 |
+
}
|
469 |
+
},
|
470 |
+
"xnli_zh": {
|
471 |
+
"task": "xnli_zh",
|
472 |
+
"group": "xnli",
|
473 |
+
"dataset_path": "xnli",
|
474 |
+
"dataset_name": "zh",
|
475 |
+
"training_split": "train",
|
476 |
+
"validation_split": "validation",
|
477 |
+
"doc_to_text": "",
|
478 |
+
"doc_to_target": "label",
|
479 |
+
"doc_to_choice": "{{[premise+\", 正确? 是的, \"+hypothesis,premise+\", 正确? 所以, \"+hypothesis,premise+\", 正确? 不是的, \"+hypothesis]}}",
|
480 |
+
"description": "",
|
481 |
+
"target_delimiter": " ",
|
482 |
+
"fewshot_delimiter": "\n\n",
|
483 |
+
"metric_list": [
|
484 |
+
{
|
485 |
+
"metric": "acc",
|
486 |
+
"aggregation": "mean",
|
487 |
+
"higher_is_better": true
|
488 |
+
}
|
489 |
+
],
|
490 |
+
"output_type": "multiple_choice",
|
491 |
+
"repeats": 1,
|
492 |
+
"should_decontaminate": false,
|
493 |
+
"metadata": {
|
494 |
+
"version": 1.0
|
495 |
+
}
|
496 |
+
}
|
497 |
+
},
|
498 |
+
"versions": {
|
499 |
+
"xnli": "N/A",
|
500 |
+
"xnli_ar": 1.0,
|
501 |
+
"xnli_bg": 1.0,
|
502 |
+
"xnli_de": 1.0,
|
503 |
+
"xnli_el": 1.0,
|
504 |
+
"xnli_en": 1.0,
|
505 |
+
"xnli_es": 1.0,
|
506 |
+
"xnli_fr": 1.0,
|
507 |
+
"xnli_hi": 1.0,
|
508 |
+
"xnli_ru": 1.0,
|
509 |
+
"xnli_sw": 1.0,
|
510 |
+
"xnli_th": 1.0,
|
511 |
+
"xnli_tr": 1.0,
|
512 |
+
"xnli_ur": 1.0,
|
513 |
+
"xnli_vi": 1.0,
|
514 |
+
"xnli_zh": 1.0
|
515 |
+
},
|
516 |
+
"n-shot": {
|
517 |
+
"xnli": 0,
|
518 |
+
"xnli_ar": 0,
|
519 |
+
"xnli_bg": 0,
|
520 |
+
"xnli_de": 0,
|
521 |
+
"xnli_el": 0,
|
522 |
+
"xnli_en": 0,
|
523 |
+
"xnli_es": 0,
|
524 |
+
"xnli_fr": 0,
|
525 |
+
"xnli_hi": 0,
|
526 |
+
"xnli_ru": 0,
|
527 |
+
"xnli_sw": 0,
|
528 |
+
"xnli_th": 0,
|
529 |
+
"xnli_tr": 0,
|
530 |
+
"xnli_ur": 0,
|
531 |
+
"xnli_vi": 0,
|
532 |
+
"xnli_zh": 0
|
533 |
+
},
|
534 |
+
"config": {
|
535 |
+
"model": "hf",
|
536 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
537 |
+
"batch_size": "auto",
|
538 |
+
"batch_sizes": [
|
539 |
+
16
|
540 |
+
],
|
541 |
+
"device": null,
|
542 |
+
"use_cache": null,
|
543 |
+
"limit": null,
|
544 |
+
"bootstrap_iters": 100000,
|
545 |
+
"gen_kwargs": null
|
546 |
+
},
|
547 |
+
"git_hash": "9b1cd24"
|
548 |
+
}
|
lm-eval-output/huggyllama/llama-7b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b070e6e7185c6c880ca2997c77499c347f243d6c89480cf5d8a43601529ab45a
|
3 |
+
size 179982
|
lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:06bb427a580eee30342b22c99f6d903395d6c06552f2e9178d714fb9d3706be1
|
3 |
+
size 4415514
|
lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,423 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"xstorycloze": {
|
4 |
+
"acc,none": 0.5594729558991636,
|
5 |
+
"acc_stderr,none": 0.0737928797468809,
|
6 |
+
"alias": "xstorycloze"
|
7 |
+
},
|
8 |
+
"xstorycloze_ar": {
|
9 |
+
"acc,none": 0.48444738583719393,
|
10 |
+
"acc_stderr,none": 0.012860899111470791,
|
11 |
+
"alias": " - xstorycloze_ar"
|
12 |
+
},
|
13 |
+
"xstorycloze_en": {
|
14 |
+
"acc,none": 0.7657180675049636,
|
15 |
+
"acc_stderr,none": 0.010899720775371961,
|
16 |
+
"alias": " - xstorycloze_en"
|
17 |
+
},
|
18 |
+
"xstorycloze_es": {
|
19 |
+
"acc,none": 0.6578424884182661,
|
20 |
+
"acc_stderr,none": 0.012209152707472842,
|
21 |
+
"alias": " - xstorycloze_es"
|
22 |
+
},
|
23 |
+
"xstorycloze_eu": {
|
24 |
+
"acc,none": 0.4990072799470549,
|
25 |
+
"acc_stderr,none": 0.012867099955422921,
|
26 |
+
"alias": " - xstorycloze_eu"
|
27 |
+
},
|
28 |
+
"xstorycloze_hi": {
|
29 |
+
"acc,none": 0.5254798146922568,
|
30 |
+
"acc_stderr,none": 0.012850407240776846,
|
31 |
+
"alias": " - xstorycloze_hi"
|
32 |
+
},
|
33 |
+
"xstorycloze_id": {
|
34 |
+
"acc,none": 0.5268034414295168,
|
35 |
+
"acc_stderr,none": 0.012848623899505768,
|
36 |
+
"alias": " - xstorycloze_id"
|
37 |
+
},
|
38 |
+
"xstorycloze_my": {
|
39 |
+
"acc,none": 0.48378557246856385,
|
40 |
+
"acc_stderr,none": 0.012860357805055867,
|
41 |
+
"alias": " - xstorycloze_my"
|
42 |
+
},
|
43 |
+
"xstorycloze_ru": {
|
44 |
+
"acc,none": 0.6221045665122436,
|
45 |
+
"acc_stderr,none": 0.01247754207299466,
|
46 |
+
"alias": " - xstorycloze_ru"
|
47 |
+
},
|
48 |
+
"xstorycloze_sw": {
|
49 |
+
"acc,none": 0.5076108537392455,
|
50 |
+
"acc_stderr,none": 0.012865634571114485,
|
51 |
+
"alias": " - xstorycloze_sw"
|
52 |
+
},
|
53 |
+
"xstorycloze_te": {
|
54 |
+
"acc,none": 0.5314361350099271,
|
55 |
+
"acc_stderr,none": 0.012841668760976905,
|
56 |
+
"alias": " - xstorycloze_te"
|
57 |
+
},
|
58 |
+
"xstorycloze_zh": {
|
59 |
+
"acc,none": 0.5499669093315684,
|
60 |
+
"acc_stderr,none": 0.012802713598219839,
|
61 |
+
"alias": " - xstorycloze_zh"
|
62 |
+
}
|
63 |
+
},
|
64 |
+
"groups": {
|
65 |
+
"xstorycloze": {
|
66 |
+
"acc,none": 0.5594729558991636,
|
67 |
+
"acc_stderr,none": 0.0737928797468809,
|
68 |
+
"alias": "xstorycloze"
|
69 |
+
}
|
70 |
+
},
|
71 |
+
"configs": {
|
72 |
+
"xstorycloze_ar": {
|
73 |
+
"task": "xstorycloze_ar",
|
74 |
+
"group": "xstorycloze",
|
75 |
+
"dataset_path": "juletxara/xstory_cloze",
|
76 |
+
"dataset_name": "ar",
|
77 |
+
"training_split": "train",
|
78 |
+
"validation_split": "eval",
|
79 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
80 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
81 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
82 |
+
"description": "",
|
83 |
+
"target_delimiter": " ",
|
84 |
+
"fewshot_delimiter": "\n\n",
|
85 |
+
"metric_list": [
|
86 |
+
{
|
87 |
+
"metric": "acc",
|
88 |
+
"aggregation": "mean",
|
89 |
+
"higher_is_better": true
|
90 |
+
}
|
91 |
+
],
|
92 |
+
"output_type": "multiple_choice",
|
93 |
+
"repeats": 1,
|
94 |
+
"should_decontaminate": true,
|
95 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
96 |
+
"metadata": {
|
97 |
+
"version": 1.0
|
98 |
+
}
|
99 |
+
},
|
100 |
+
"xstorycloze_en": {
|
101 |
+
"task": "xstorycloze_en",
|
102 |
+
"group": "xstorycloze",
|
103 |
+
"dataset_path": "juletxara/xstory_cloze",
|
104 |
+
"dataset_name": "en",
|
105 |
+
"training_split": "train",
|
106 |
+
"validation_split": "eval",
|
107 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
108 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
109 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
110 |
+
"description": "",
|
111 |
+
"target_delimiter": " ",
|
112 |
+
"fewshot_delimiter": "\n\n",
|
113 |
+
"metric_list": [
|
114 |
+
{
|
115 |
+
"metric": "acc",
|
116 |
+
"aggregation": "mean",
|
117 |
+
"higher_is_better": true
|
118 |
+
}
|
119 |
+
],
|
120 |
+
"output_type": "multiple_choice",
|
121 |
+
"repeats": 1,
|
122 |
+
"should_decontaminate": true,
|
123 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
124 |
+
"metadata": {
|
125 |
+
"version": 1.0
|
126 |
+
}
|
127 |
+
},
|
128 |
+
"xstorycloze_es": {
|
129 |
+
"task": "xstorycloze_es",
|
130 |
+
"group": "xstorycloze",
|
131 |
+
"dataset_path": "juletxara/xstory_cloze",
|
132 |
+
"dataset_name": "es",
|
133 |
+
"training_split": "train",
|
134 |
+
"validation_split": "eval",
|
135 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
136 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
137 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
138 |
+
"description": "",
|
139 |
+
"target_delimiter": " ",
|
140 |
+
"fewshot_delimiter": "\n\n",
|
141 |
+
"metric_list": [
|
142 |
+
{
|
143 |
+
"metric": "acc",
|
144 |
+
"aggregation": "mean",
|
145 |
+
"higher_is_better": true
|
146 |
+
}
|
147 |
+
],
|
148 |
+
"output_type": "multiple_choice",
|
149 |
+
"repeats": 1,
|
150 |
+
"should_decontaminate": true,
|
151 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
152 |
+
"metadata": {
|
153 |
+
"version": 1.0
|
154 |
+
}
|
155 |
+
},
|
156 |
+
"xstorycloze_eu": {
|
157 |
+
"task": "xstorycloze_eu",
|
158 |
+
"group": "xstorycloze",
|
159 |
+
"dataset_path": "juletxara/xstory_cloze",
|
160 |
+
"dataset_name": "eu",
|
161 |
+
"training_split": "train",
|
162 |
+
"validation_split": "eval",
|
163 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
164 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
165 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
166 |
+
"description": "",
|
167 |
+
"target_delimiter": " ",
|
168 |
+
"fewshot_delimiter": "\n\n",
|
169 |
+
"metric_list": [
|
170 |
+
{
|
171 |
+
"metric": "acc",
|
172 |
+
"aggregation": "mean",
|
173 |
+
"higher_is_better": true
|
174 |
+
}
|
175 |
+
],
|
176 |
+
"output_type": "multiple_choice",
|
177 |
+
"repeats": 1,
|
178 |
+
"should_decontaminate": true,
|
179 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
180 |
+
"metadata": {
|
181 |
+
"version": 1.0
|
182 |
+
}
|
183 |
+
},
|
184 |
+
"xstorycloze_hi": {
|
185 |
+
"task": "xstorycloze_hi",
|
186 |
+
"group": "xstorycloze",
|
187 |
+
"dataset_path": "juletxara/xstory_cloze",
|
188 |
+
"dataset_name": "hi",
|
189 |
+
"training_split": "train",
|
190 |
+
"validation_split": "eval",
|
191 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
192 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
193 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
194 |
+
"description": "",
|
195 |
+
"target_delimiter": " ",
|
196 |
+
"fewshot_delimiter": "\n\n",
|
197 |
+
"metric_list": [
|
198 |
+
{
|
199 |
+
"metric": "acc",
|
200 |
+
"aggregation": "mean",
|
201 |
+
"higher_is_better": true
|
202 |
+
}
|
203 |
+
],
|
204 |
+
"output_type": "multiple_choice",
|
205 |
+
"repeats": 1,
|
206 |
+
"should_decontaminate": true,
|
207 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
208 |
+
"metadata": {
|
209 |
+
"version": 1.0
|
210 |
+
}
|
211 |
+
},
|
212 |
+
"xstorycloze_id": {
|
213 |
+
"task": "xstorycloze_id",
|
214 |
+
"group": "xstorycloze",
|
215 |
+
"dataset_path": "juletxara/xstory_cloze",
|
216 |
+
"dataset_name": "id",
|
217 |
+
"training_split": "train",
|
218 |
+
"validation_split": "eval",
|
219 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
220 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
221 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
222 |
+
"description": "",
|
223 |
+
"target_delimiter": " ",
|
224 |
+
"fewshot_delimiter": "\n\n",
|
225 |
+
"metric_list": [
|
226 |
+
{
|
227 |
+
"metric": "acc",
|
228 |
+
"aggregation": "mean",
|
229 |
+
"higher_is_better": true
|
230 |
+
}
|
231 |
+
],
|
232 |
+
"output_type": "multiple_choice",
|
233 |
+
"repeats": 1,
|
234 |
+
"should_decontaminate": true,
|
235 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
236 |
+
"metadata": {
|
237 |
+
"version": 1.0
|
238 |
+
}
|
239 |
+
},
|
240 |
+
"xstorycloze_my": {
|
241 |
+
"task": "xstorycloze_my",
|
242 |
+
"group": "xstorycloze",
|
243 |
+
"dataset_path": "juletxara/xstory_cloze",
|
244 |
+
"dataset_name": "my",
|
245 |
+
"training_split": "train",
|
246 |
+
"validation_split": "eval",
|
247 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
248 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
249 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
250 |
+
"description": "",
|
251 |
+
"target_delimiter": " ",
|
252 |
+
"fewshot_delimiter": "\n\n",
|
253 |
+
"metric_list": [
|
254 |
+
{
|
255 |
+
"metric": "acc",
|
256 |
+
"aggregation": "mean",
|
257 |
+
"higher_is_better": true
|
258 |
+
}
|
259 |
+
],
|
260 |
+
"output_type": "multiple_choice",
|
261 |
+
"repeats": 1,
|
262 |
+
"should_decontaminate": true,
|
263 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
264 |
+
"metadata": {
|
265 |
+
"version": 1.0
|
266 |
+
}
|
267 |
+
},
|
268 |
+
"xstorycloze_ru": {
|
269 |
+
"task": "xstorycloze_ru",
|
270 |
+
"group": "xstorycloze",
|
271 |
+
"dataset_path": "juletxara/xstory_cloze",
|
272 |
+
"dataset_name": "ru",
|
273 |
+
"training_split": "train",
|
274 |
+
"validation_split": "eval",
|
275 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
276 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
277 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
278 |
+
"description": "",
|
279 |
+
"target_delimiter": " ",
|
280 |
+
"fewshot_delimiter": "\n\n",
|
281 |
+
"metric_list": [
|
282 |
+
{
|
283 |
+
"metric": "acc",
|
284 |
+
"aggregation": "mean",
|
285 |
+
"higher_is_better": true
|
286 |
+
}
|
287 |
+
],
|
288 |
+
"output_type": "multiple_choice",
|
289 |
+
"repeats": 1,
|
290 |
+
"should_decontaminate": true,
|
291 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
292 |
+
"metadata": {
|
293 |
+
"version": 1.0
|
294 |
+
}
|
295 |
+
},
|
296 |
+
"xstorycloze_sw": {
|
297 |
+
"task": "xstorycloze_sw",
|
298 |
+
"group": "xstorycloze",
|
299 |
+
"dataset_path": "juletxara/xstory_cloze",
|
300 |
+
"dataset_name": "sw",
|
301 |
+
"training_split": "train",
|
302 |
+
"validation_split": "eval",
|
303 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
304 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
305 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
306 |
+
"description": "",
|
307 |
+
"target_delimiter": " ",
|
308 |
+
"fewshot_delimiter": "\n\n",
|
309 |
+
"metric_list": [
|
310 |
+
{
|
311 |
+
"metric": "acc",
|
312 |
+
"aggregation": "mean",
|
313 |
+
"higher_is_better": true
|
314 |
+
}
|
315 |
+
],
|
316 |
+
"output_type": "multiple_choice",
|
317 |
+
"repeats": 1,
|
318 |
+
"should_decontaminate": true,
|
319 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
320 |
+
"metadata": {
|
321 |
+
"version": 1.0
|
322 |
+
}
|
323 |
+
},
|
324 |
+
"xstorycloze_te": {
|
325 |
+
"task": "xstorycloze_te",
|
326 |
+
"group": "xstorycloze",
|
327 |
+
"dataset_path": "juletxara/xstory_cloze",
|
328 |
+
"dataset_name": "te",
|
329 |
+
"training_split": "train",
|
330 |
+
"validation_split": "eval",
|
331 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
332 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
333 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
334 |
+
"description": "",
|
335 |
+
"target_delimiter": " ",
|
336 |
+
"fewshot_delimiter": "\n\n",
|
337 |
+
"metric_list": [
|
338 |
+
{
|
339 |
+
"metric": "acc",
|
340 |
+
"aggregation": "mean",
|
341 |
+
"higher_is_better": true
|
342 |
+
}
|
343 |
+
],
|
344 |
+
"output_type": "multiple_choice",
|
345 |
+
"repeats": 1,
|
346 |
+
"should_decontaminate": true,
|
347 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
348 |
+
"metadata": {
|
349 |
+
"version": 1.0
|
350 |
+
}
|
351 |
+
},
|
352 |
+
"xstorycloze_zh": {
|
353 |
+
"task": "xstorycloze_zh",
|
354 |
+
"group": "xstorycloze",
|
355 |
+
"dataset_path": "juletxara/xstory_cloze",
|
356 |
+
"dataset_name": "zh",
|
357 |
+
"training_split": "train",
|
358 |
+
"validation_split": "eval",
|
359 |
+
"doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
360 |
+
"doc_to_target": "{{answer_right_ending-1}}",
|
361 |
+
"doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
|
362 |
+
"description": "",
|
363 |
+
"target_delimiter": " ",
|
364 |
+
"fewshot_delimiter": "\n\n",
|
365 |
+
"metric_list": [
|
366 |
+
{
|
367 |
+
"metric": "acc",
|
368 |
+
"aggregation": "mean",
|
369 |
+
"higher_is_better": true
|
370 |
+
}
|
371 |
+
],
|
372 |
+
"output_type": "multiple_choice",
|
373 |
+
"repeats": 1,
|
374 |
+
"should_decontaminate": true,
|
375 |
+
"doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
|
376 |
+
"metadata": {
|
377 |
+
"version": 1.0
|
378 |
+
}
|
379 |
+
}
|
380 |
+
},
|
381 |
+
"versions": {
|
382 |
+
"xstorycloze": "N/A",
|
383 |
+
"xstorycloze_ar": 1.0,
|
384 |
+
"xstorycloze_en": 1.0,
|
385 |
+
"xstorycloze_es": 1.0,
|
386 |
+
"xstorycloze_eu": 1.0,
|
387 |
+
"xstorycloze_hi": 1.0,
|
388 |
+
"xstorycloze_id": 1.0,
|
389 |
+
"xstorycloze_my": 1.0,
|
390 |
+
"xstorycloze_ru": 1.0,
|
391 |
+
"xstorycloze_sw": 1.0,
|
392 |
+
"xstorycloze_te": 1.0,
|
393 |
+
"xstorycloze_zh": 1.0
|
394 |
+
},
|
395 |
+
"n-shot": {
|
396 |
+
"xstorycloze": 0,
|
397 |
+
"xstorycloze_ar": 0,
|
398 |
+
"xstorycloze_en": 0,
|
399 |
+
"xstorycloze_es": 0,
|
400 |
+
"xstorycloze_eu": 0,
|
401 |
+
"xstorycloze_hi": 0,
|
402 |
+
"xstorycloze_id": 0,
|
403 |
+
"xstorycloze_my": 0,
|
404 |
+
"xstorycloze_ru": 0,
|
405 |
+
"xstorycloze_sw": 0,
|
406 |
+
"xstorycloze_te": 0,
|
407 |
+
"xstorycloze_zh": 0
|
408 |
+
},
|
409 |
+
"config": {
|
410 |
+
"model": "hf",
|
411 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
412 |
+
"batch_size": "auto",
|
413 |
+
"batch_sizes": [
|
414 |
+
8
|
415 |
+
],
|
416 |
+
"device": null,
|
417 |
+
"use_cache": null,
|
418 |
+
"limit": null,
|
419 |
+
"bootstrap_iters": 100000,
|
420 |
+
"gen_kwargs": null
|
421 |
+
},
|
422 |
+
"git_hash": "9b1cd24"
|
423 |
+
}
|
lm-eval-output/huggyllama/llama-7b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:dd307979e78e81a7c67d5382b4b799268fbc747cb7a3b14753524853f9052358
|
3 |
+
size 45665
|
lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ed5d5ab6595623f1188a5b64004801c5494876b68d4442cc20a8bc024439ccb5
|
3 |
+
size 606624
|
lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
ADDED
@@ -0,0 +1,248 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"results": {
|
3 |
+
"xwinograd": {
|
4 |
+
"acc,none": 0.7597212856821758,
|
5 |
+
"acc_stderr,none": 0.07621979232315931,
|
6 |
+
"alias": "xwinograd"
|
7 |
+
},
|
8 |
+
"xwinograd_en": {
|
9 |
+
"acc,none": 0.88,
|
10 |
+
"acc_stderr,none": 0.006740838111907554,
|
11 |
+
"alias": " - xwinograd_en"
|
12 |
+
},
|
13 |
+
"xwinograd_fr": {
|
14 |
+
"acc,none": 0.6987951807228916,
|
15 |
+
"acc_stderr,none": 0.05066394254941721,
|
16 |
+
"alias": " - xwinograd_fr"
|
17 |
+
},
|
18 |
+
"xwinograd_jp": {
|
19 |
+
"acc,none": 0.5922836287799792,
|
20 |
+
"acc_stderr,none": 0.015876734592302294,
|
21 |
+
"alias": " - xwinograd_jp"
|
22 |
+
},
|
23 |
+
"xwinograd_pt": {
|
24 |
+
"acc,none": 0.7300380228136882,
|
25 |
+
"acc_stderr,none": 0.027426689796728774,
|
26 |
+
"alias": " - xwinograd_pt"
|
27 |
+
},
|
28 |
+
"xwinograd_ru": {
|
29 |
+
"acc,none": 0.6317460317460317,
|
30 |
+
"acc_stderr,none": 0.027219500732466696,
|
31 |
+
"alias": " - xwinograd_ru"
|
32 |
+
},
|
33 |
+
"xwinograd_zh": {
|
34 |
+
"acc,none": 0.628968253968254,
|
35 |
+
"acc_stderr,none": 0.02153951426767635,
|
36 |
+
"alias": " - xwinograd_zh"
|
37 |
+
}
|
38 |
+
},
|
39 |
+
"groups": {
|
40 |
+
"xwinograd": {
|
41 |
+
"acc,none": 0.7597212856821758,
|
42 |
+
"acc_stderr,none": 0.07621979232315931,
|
43 |
+
"alias": "xwinograd"
|
44 |
+
}
|
45 |
+
},
|
46 |
+
"configs": {
|
47 |
+
"xwinograd_en": {
|
48 |
+
"task": "xwinograd_en",
|
49 |
+
"group": [
|
50 |
+
"xwinograd"
|
51 |
+
],
|
52 |
+
"dataset_path": "Muennighoff/xwinograd",
|
53 |
+
"dataset_name": "en",
|
54 |
+
"test_split": "test",
|
55 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
56 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
57 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
58 |
+
"description": "",
|
59 |
+
"target_delimiter": " ",
|
60 |
+
"fewshot_delimiter": "\n\n",
|
61 |
+
"metric_list": [
|
62 |
+
{
|
63 |
+
"metric": "acc",
|
64 |
+
"aggregation": "mean",
|
65 |
+
"higher_is_better": true
|
66 |
+
}
|
67 |
+
],
|
68 |
+
"output_type": "multiple_choice",
|
69 |
+
"repeats": 1,
|
70 |
+
"should_decontaminate": false,
|
71 |
+
"metadata": {
|
72 |
+
"version": 1.0
|
73 |
+
}
|
74 |
+
},
|
75 |
+
"xwinograd_fr": {
|
76 |
+
"task": "xwinograd_fr",
|
77 |
+
"group": [
|
78 |
+
"xwinograd"
|
79 |
+
],
|
80 |
+
"dataset_path": "Muennighoff/xwinograd",
|
81 |
+
"dataset_name": "fr",
|
82 |
+
"test_split": "test",
|
83 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
84 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
85 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
86 |
+
"description": "",
|
87 |
+
"target_delimiter": " ",
|
88 |
+
"fewshot_delimiter": "\n\n",
|
89 |
+
"metric_list": [
|
90 |
+
{
|
91 |
+
"metric": "acc",
|
92 |
+
"aggregation": "mean",
|
93 |
+
"higher_is_better": true
|
94 |
+
}
|
95 |
+
],
|
96 |
+
"output_type": "multiple_choice",
|
97 |
+
"repeats": 1,
|
98 |
+
"should_decontaminate": false,
|
99 |
+
"metadata": {
|
100 |
+
"version": 1.0
|
101 |
+
}
|
102 |
+
},
|
103 |
+
"xwinograd_jp": {
|
104 |
+
"task": "xwinograd_jp",
|
105 |
+
"group": [
|
106 |
+
"xwinograd"
|
107 |
+
],
|
108 |
+
"dataset_path": "Muennighoff/xwinograd",
|
109 |
+
"dataset_name": "jp",
|
110 |
+
"test_split": "test",
|
111 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
112 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
113 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
114 |
+
"description": "",
|
115 |
+
"target_delimiter": " ",
|
116 |
+
"fewshot_delimiter": "\n\n",
|
117 |
+
"metric_list": [
|
118 |
+
{
|
119 |
+
"metric": "acc",
|
120 |
+
"aggregation": "mean",
|
121 |
+
"higher_is_better": true
|
122 |
+
}
|
123 |
+
],
|
124 |
+
"output_type": "multiple_choice",
|
125 |
+
"repeats": 1,
|
126 |
+
"should_decontaminate": false,
|
127 |
+
"metadata": {
|
128 |
+
"version": 1.0
|
129 |
+
}
|
130 |
+
},
|
131 |
+
"xwinograd_pt": {
|
132 |
+
"task": "xwinograd_pt",
|
133 |
+
"group": [
|
134 |
+
"xwinograd"
|
135 |
+
],
|
136 |
+
"dataset_path": "Muennighoff/xwinograd",
|
137 |
+
"dataset_name": "pt",
|
138 |
+
"test_split": "test",
|
139 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
140 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
141 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
142 |
+
"description": "",
|
143 |
+
"target_delimiter": " ",
|
144 |
+
"fewshot_delimiter": "\n\n",
|
145 |
+
"metric_list": [
|
146 |
+
{
|
147 |
+
"metric": "acc",
|
148 |
+
"aggregation": "mean",
|
149 |
+
"higher_is_better": true
|
150 |
+
}
|
151 |
+
],
|
152 |
+
"output_type": "multiple_choice",
|
153 |
+
"repeats": 1,
|
154 |
+
"should_decontaminate": false,
|
155 |
+
"metadata": {
|
156 |
+
"version": 1.0
|
157 |
+
}
|
158 |
+
},
|
159 |
+
"xwinograd_ru": {
|
160 |
+
"task": "xwinograd_ru",
|
161 |
+
"group": [
|
162 |
+
"xwinograd"
|
163 |
+
],
|
164 |
+
"dataset_path": "Muennighoff/xwinograd",
|
165 |
+
"dataset_name": "ru",
|
166 |
+
"test_split": "test",
|
167 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
168 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
169 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
170 |
+
"description": "",
|
171 |
+
"target_delimiter": " ",
|
172 |
+
"fewshot_delimiter": "\n\n",
|
173 |
+
"metric_list": [
|
174 |
+
{
|
175 |
+
"metric": "acc",
|
176 |
+
"aggregation": "mean",
|
177 |
+
"higher_is_better": true
|
178 |
+
}
|
179 |
+
],
|
180 |
+
"output_type": "multiple_choice",
|
181 |
+
"repeats": 1,
|
182 |
+
"should_decontaminate": false,
|
183 |
+
"metadata": {
|
184 |
+
"version": 1.0
|
185 |
+
}
|
186 |
+
},
|
187 |
+
"xwinograd_zh": {
|
188 |
+
"task": "xwinograd_zh",
|
189 |
+
"group": [
|
190 |
+
"xwinograd"
|
191 |
+
],
|
192 |
+
"dataset_path": "Muennighoff/xwinograd",
|
193 |
+
"dataset_name": "zh",
|
194 |
+
"test_split": "test",
|
195 |
+
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
196 |
+
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
197 |
+
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
198 |
+
"description": "",
|
199 |
+
"target_delimiter": " ",
|
200 |
+
"fewshot_delimiter": "\n\n",
|
201 |
+
"metric_list": [
|
202 |
+
{
|
203 |
+
"metric": "acc",
|
204 |
+
"aggregation": "mean",
|
205 |
+
"higher_is_better": true
|
206 |
+
}
|
207 |
+
],
|
208 |
+
"output_type": "multiple_choice",
|
209 |
+
"repeats": 1,
|
210 |
+
"should_decontaminate": false,
|
211 |
+
"metadata": {
|
212 |
+
"version": 1.0
|
213 |
+
}
|
214 |
+
}
|
215 |
+
},
|
216 |
+
"versions": {
|
217 |
+
"xwinograd": "N/A",
|
218 |
+
"xwinograd_en": 1.0,
|
219 |
+
"xwinograd_fr": 1.0,
|
220 |
+
"xwinograd_jp": 1.0,
|
221 |
+
"xwinograd_pt": 1.0,
|
222 |
+
"xwinograd_ru": 1.0,
|
223 |
+
"xwinograd_zh": 1.0
|
224 |
+
},
|
225 |
+
"n-shot": {
|
226 |
+
"xwinograd": 0,
|
227 |
+
"xwinograd_en": 0,
|
228 |
+
"xwinograd_fr": 0,
|
229 |
+
"xwinograd_jp": 0,
|
230 |
+
"xwinograd_pt": 0,
|
231 |
+
"xwinograd_ru": 0,
|
232 |
+
"xwinograd_zh": 0
|
233 |
+
},
|
234 |
+
"config": {
|
235 |
+
"model": "hf",
|
236 |
+
"model_args": "pretrained=huggyllama/llama-7b,dtype=bfloat16,trust_remote_code=True",
|
237 |
+
"batch_size": "auto",
|
238 |
+
"batch_sizes": [
|
239 |
+
32
|
240 |
+
],
|
241 |
+
"device": null,
|
242 |
+
"use_cache": null,
|
243 |
+
"limit": null,
|
244 |
+
"bootstrap_iters": 100000,
|
245 |
+
"gen_kwargs": null
|
246 |
+
},
|
247 |
+
"git_hash": "9b1cd24"
|
248 |
+
}
|
lm-eval-output/huggyllama/llama-7b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ce6fb59079d066e20a80464d99eb987dde5588c40eb826ca5ddd5b9fd713ff7c
|
3 |
+
size 37738
|