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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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- generated_from_trainer |
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model-index: |
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- name: zephyr-7b-dpo-lora |
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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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# zephyr-7b-dpo-lora |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5381 |
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- Rewards/chosen: -0.0977 |
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- Rewards/rejected: -0.7746 |
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- Rewards/accuracies: 0.7183 |
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- Rewards/margins: 0.6768 |
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- Logps/rejected: -237.3503 |
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- Logps/chosen: -283.6626 |
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- Logits/rejected: -1.8216 |
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- Logits/chosen: -1.9102 |
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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: 5e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 32 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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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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| 0.5546 | 1.0 | 968 | 0.5678 | -0.0091 | -0.4982 | 0.7054 | 0.4891 | -234.5862 | -282.7758 | -1.8508 | -1.9394 | |
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| 0.5491 | 2.0 | 1936 | 0.5438 | -0.0836 | -0.7251 | 0.7192 | 0.6414 | -236.8553 | -283.5217 | -1.8279 | -1.9162 | |
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| 0.5463 | 3.0 | 2904 | 0.5381 | -0.0977 | -0.7746 | 0.7183 | 0.6768 | -237.3503 | -283.6626 | -1.8216 | -1.9102 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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