Model save

README.md

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+---
+base_model: klue/roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: reward-bert-duplicate-answer-300
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# reward-bert-duplicate-answer-300
+
+This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2419
+- Accuracy: 0.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 9e-05
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 2023
+- gradient_accumulation_steps: 10
+- total_train_batch_size: 60
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5015        | 0.17  | 100  | 0.5284          | 0.0      |
+| 0.4259        | 0.34  | 200  | 0.3848          | 0.0      |
+| 0.3808        | 0.51  | 300  | 0.2962          | 0.0      |
+| 0.3328        | 0.69  | 400  | 0.2592          | 0.0      |
+| 0.2086        | 0.86  | 500  | 0.2419          | 0.0      |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.1+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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