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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: RewardModel_RobertaBase |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# RewardModel_RobertaBase |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5050 |
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- F1: 0.7522 |
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- Roc Auc: 0.7526 |
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- Accuracy: 0.7509 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.6464 | 1.0 | 100 | 0.6186 | 0.6772 | 0.6772 | 0.6737 | |
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| 0.5776 | 2.0 | 200 | 0.5439 | 0.7298 | 0.7298 | 0.7298 | |
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| 0.4806 | 3.0 | 300 | 0.5050 | 0.7522 | 0.7526 | 0.7509 | |
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| 0.3909 | 4.0 | 400 | 0.8594 | 0.6690 | 0.6684 | 0.6667 | |
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| 0.331 | 5.0 | 500 | 0.7766 | 0.7206 | 0.7211 | 0.7193 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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