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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: 400STEPS_1e7rate_01beta_T5 |
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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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# 400STEPS_1e7rate_01beta_T5 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6483 |
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- Rewards/chosen: -0.0026 |
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- Rewards/rejected: -0.1019 |
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- Rewards/accuracies: 0.6593 |
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- Rewards/margins: 0.0994 |
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- Logps/rejected: -15.7387 |
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- Logps/chosen: -12.9908 |
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- Logits/rejected: -3.1652 |
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- Logits/chosen: -3.1650 |
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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: 1e-07 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 400 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6916 | 0.1 | 50 | 0.6908 | 0.0048 | 0.0002 | 0.5670 | 0.0047 | -14.7176 | -12.9168 | -3.1591 | -3.1588 | |
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| 0.6821 | 0.2 | 100 | 0.6764 | 0.0187 | -0.0159 | 0.6681 | 0.0346 | -14.8782 | -12.7778 | -3.1625 | -3.1622 | |
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| 0.6647 | 0.29 | 150 | 0.6629 | 0.0225 | -0.0422 | 0.6659 | 0.0648 | -15.1414 | -12.7399 | -3.1625 | -3.1623 | |
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| 0.6536 | 0.39 | 200 | 0.6552 | 0.0148 | -0.0679 | 0.6505 | 0.0827 | -15.3987 | -12.8175 | -3.1657 | -3.1654 | |
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| 0.6354 | 0.49 | 250 | 0.6509 | 0.0022 | -0.0909 | 0.6593 | 0.0931 | -15.6282 | -12.9431 | -3.1646 | -3.1643 | |
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| 0.6468 | 0.59 | 300 | 0.6484 | -0.0022 | -0.1013 | 0.6527 | 0.0991 | -15.7319 | -12.9869 | -3.1653 | -3.1650 | |
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| 0.6549 | 0.68 | 350 | 0.6481 | -0.0021 | -0.1019 | 0.6571 | 0.0998 | -15.7386 | -12.9865 | -3.1652 | -3.1650 | |
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| 0.6684 | 0.78 | 400 | 0.6483 | -0.0026 | -0.1019 | 0.6593 | 0.0994 | -15.7387 | -12.9908 | -3.1652 | -3.1650 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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