Laseung/roberta-base-klue-ynat-classification

README.md

@@ -17,8 +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: 0.4450
-- Accuracy: 0.872
+- Loss: 0.4444
+- Accuracy: 0.864
 
 ## Model description
 
@@ -41,7 +41,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 1
 
@@ -49,12 +49,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.551         | 1.0   | 1250 | 0.5041          | 0.854    |
+| 0.5365        | 1.0   | 1250 | 0.5129          | 0.848    |
 
 
 ### Framework versions
 
-- Transformers 4.50.0
+- Transformers 4.57.1
 - Pytorch 2.8.0+cu126
-- Datasets 3.5.0
-- Tokenizers 0.21.4
+- Datasets 4.0.0
+- Tokenizers 0.22.1

config.json

@@ -5,6 +5,7 @@
   "attention_probs_dropout_prob": 0.1,
   "bos_token_id": 0,
   "classifier_dropout": null,
+  "dtype": "float32",
   "eos_token_id": 2,
   "gradient_checkpointing": false,
   "hidden_act": "gelu",
@@ -39,8 +40,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "tokenizer_class": "BertTokenizer",
-  "torch_dtype": "float32",
-  "transformers_version": "4.50.0",
+  "transformers_version": "4.57.1",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 32000

model.safetensors

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training_args.bin

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