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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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- orpo |
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- generated_from_trainer |
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model-index: |
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- name: mistral-orpo-mix-b0.05-l1024-pl512-lr5e-7-cosine |
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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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# mistral-orpo-mix-b0.05-l1024-pl512-lr5e-7-cosine |
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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: 0.8648 |
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- Rewards/chosen: -0.0405 |
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- Rewards/rejected: -0.0502 |
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- Rewards/accuracies: 0.6458 |
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- Rewards/margins: 0.0097 |
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- Logps/rejected: -1.0036 |
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- Logps/chosen: -0.8096 |
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- Logits/rejected: -2.9146 |
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- Logits/chosen: -2.9040 |
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- Nll Loss: 0.8392 |
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- Log Odds Ratio: -0.6215 |
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- Log Odds Chosen: 0.3802 |
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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: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 100 |
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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 | Nll Loss | Log Odds Ratio | Log Odds Chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:| |
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| 0.9159 | 1.0 | 105 | 0.8794 | -0.0421 | -0.0499 | 0.6302 | 0.0078 | -0.9975 | -0.8413 | -2.8931 | -2.8875 | 0.8561 | -0.6429 | 0.3024 | |
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| 0.8397 | 2.0 | 211 | 0.8612 | -0.0404 | -0.0495 | 0.6458 | 0.0092 | -0.9902 | -0.8071 | -2.8882 | -2.8794 | 0.8366 | -0.6257 | 0.3555 | |
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| 0.7808 | 2.99 | 315 | 0.8648 | -0.0405 | -0.0502 | 0.6458 | 0.0097 | -1.0036 | -0.8096 | -2.9146 | -2.9040 | 0.8392 | -0.6215 | 0.3802 | |
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### Framework versions |
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- Transformers 4.39.0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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