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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: sambar-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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# sambar-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: 0.5747 |
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- Rewards/chosen: -0.0141 |
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- Rewards/rejected: -0.4147 |
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- Rewards/accuracies: 0.7060 |
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- Rewards/margins: 0.4006 |
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- Logps/rejected: -221.3069 |
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- Logps/chosen: -263.0773 |
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- Logits/rejected: -2.1478 |
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- Logits/chosen: -2.2594 |
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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: 2 |
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- eval_batch_size: 4 |
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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: 32 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 16 |
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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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| 0.6213 | 1.0 | 242 | 0.6182 | 0.0426 | -0.1569 | 0.6860 | 0.1995 | -218.7293 | -262.5110 | -2.1605 | -2.2727 | |
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| 0.5903 | 2.0 | 484 | 0.5826 | 0.0046 | -0.3500 | 0.6940 | 0.3546 | -220.6603 | -262.8906 | -2.1517 | -2.2634 | |
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| 0.5743 | 3.0 | 726 | 0.5747 | -0.0141 | -0.4147 | 0.7060 | 0.4006 | -221.3069 | -263.0773 | -2.1478 | -2.2594 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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