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artifact.metadata

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+{
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+    "nbits": 1,
+    "kmeans_niters": 20,
+    "similarity": "l2",
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+    "accumsteps": 2,
+    "lr": 3e-6,
+    "maxsteps": 400000,
+    "save_every": null,
+    "resume": false,
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+    "warmup_bert": null,
+    "relu": false,
+    "nway": 32,
+    "use_ib_negatives": true,
+    "query_maxlen": 32,
+    "attend_to_mask_tokens": false,
+    "dim": 128,
+    "doc_maxlen": 180,
+    "mask_punctuation": true,
+    "checkpoint": "\/future\/u\/okhattab\/experiments\/MSMARCO-psg\/train.py\/msmarco.psg.l2.round2x\/checkpoints\/colbert-400000.dnn",
+    "triples": "\/future\/u\/okhattab\/root\/unit\/experiments\/2021.10\/downstream.distillation.2_score\/2021-10-17\/11.07.59\/examples.32.json.head",
+    "collection": "\/dfs\/scratch1\/okhattab\/data\/MSMARCO\/collection.tsv",
+    "queries": "\/dfs\/scratch1\/okhattab\/data\/MSMARCO\/queries.train.tsv",
+    "index_name": null,
+    "overwrite": false,
+    "root": "\/future\/u\/okhattab\/root\/unit\/experiments",
+    "experiment": "2021.10",
+    "index_root": null,
+    "name": "kld.v3.nway32.l2.ib",
+    "rank": 0,
+    "nranks": 4,
+    "amp": true,
+    "gpus": 4,
+    "meta": {
+        "hostname": "future5.stanford.edu",
+        "git_branch": "api_residual_compression3_KLD",
+        "git_hash": "8488a790c1e88a517ab6ada6cd4907b9a960eb4f",
+        "git_commit_datetime": "2021-10-17 16:37:15-07:00",
+        "current_datetime": "Oct 23, 2021 ;  4:36PM PDT (-0700)",
+        "cmd": "\/future\/u\/okhattab\/repos\/QolBERT2\/tests\/train_kld_nway32_pretrained.py",
+        "version": "colbert-v0.4"
+    }
+}

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "HF_ColBERT"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
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+  "hidden_act": "gelu",
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+  "hidden_size": 768,
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+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.10.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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