godling/roberta-base-klue-ynat-classification

README.md

@@ -1,4 +1,5 @@
 ---
+library_name: transformers
 base_model: klue/roberta-base
 tags:
 - generated_from_trainer
@@ -16,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4364
-- Accuracy: 0.857
+- Loss: 0.4595
+- Accuracy: 0.854
 
 ## Model description
 
@@ -40,7 +41,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 1
 
@@ -48,12 +49,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.5276        | 1.0   | 1250 | 0.5157          | 0.855    |
+| 0.5317        | 1.0   | 1250 | 0.5199          | 0.843    |
 
 
 ### Framework versions
 
-- Transformers 4.42.4
-- Pytorch 2.3.1+cu121
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Tokenizers 0.20.3

config.json

@@ -41,7 +41,7 @@
   "problem_type": "single_label_classification",
   "tokenizer_class": "BertTokenizer",
   "torch_dtype": "float32",
-  "transformers_version": "4.42.4",
+  "transformers_version": "4.46.2",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 32000

model.safetensors

@@ -1,3 +1,3 @@
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 size 442518124

tokenizer_config.json

@@ -42,7 +42,7 @@
     }
   },
   "bos_token": "[CLS]",
-  "clean_up_tokenization_spaces": true,
+  "clean_up_tokenization_spaces": false,
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,
   "do_lower_case": false,

training_args.bin

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