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distilroberta-base-reward-model

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: distilroberta-base
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+ tags:
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+ - trl
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+ - reward-trainer
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: reward_model
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+ results: []
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+ ---
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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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+
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+ # reward_model
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+
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+ This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5988
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+ - Accuracy: 0.65
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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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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+ - training_steps: 500
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.7043 | 0.0150 | 20 | 0.6886 | 0.54 |
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+ | 0.6671 | 0.0301 | 40 | 0.6924 | 0.53 |
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+ | 0.6131 | 0.0451 | 60 | 0.7038 | 0.58 |
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+ | 0.6149 | 0.0602 | 80 | 0.6759 | 0.6 |
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+ | 0.6539 | 0.0752 | 100 | 0.6593 | 0.58 |
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+ | 0.6671 | 0.0902 | 120 | 0.7227 | 0.59 |
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+ | 0.6863 | 0.1053 | 140 | 0.6452 | 0.58 |
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+ | 0.6332 | 0.1203 | 160 | 0.6394 | 0.64 |
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+ | 0.6259 | 0.1353 | 180 | 0.6630 | 0.61 |
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+ | 0.6257 | 0.1504 | 200 | 0.6369 | 0.61 |
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+ | 0.5376 | 0.1654 | 220 | 0.6460 | 0.62 |
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+ | 0.6734 | 0.1805 | 240 | 0.6404 | 0.62 |
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+ | 0.724 | 0.1955 | 260 | 0.7469 | 0.6 |
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+ | 0.541 | 0.2105 | 280 | 0.6295 | 0.64 |
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+ | 0.5495 | 0.2256 | 300 | 0.6182 | 0.65 |
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+ | 0.7581 | 0.2406 | 320 | 0.6262 | 0.6 |
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+ | 0.5234 | 0.2556 | 340 | 0.6228 | 0.63 |
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+ | 0.5787 | 0.2707 | 360 | 0.6208 | 0.64 |
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+ | 0.6025 | 0.2857 | 380 | 0.6069 | 0.65 |
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+ | 0.6061 | 0.3008 | 400 | 0.6166 | 0.65 |
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+ | 0.8482 | 0.3158 | 420 | 0.6078 | 0.65 |
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+ | 0.5613 | 0.3308 | 440 | 0.5940 | 0.65 |
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+ | 0.7284 | 0.3459 | 460 | 0.6042 | 0.65 |
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+ | 0.5778 | 0.3609 | 480 | 0.5990 | 0.65 |
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+ | 0.6848 | 0.3759 | 500 | 0.5988 | 0.65 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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