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--- |
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license: gemma |
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base_model: tanliboy/zephyr-7b-gemma-sft |
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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: zephyr-7b-gemma-dpo |
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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-gemma-dpo |
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This model is a fine-tuned version of [tanliboy/zephyr-7b-gemma-sft](https://huggingface.co/tanliboy/zephyr-7b-gemma-sft) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4722 |
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- Rewards/chosen: -0.0658 |
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- Rewards/rejected: -1.2673 |
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- Rewards/accuracies: 0.7396 |
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- Rewards/margins: 1.2015 |
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- Logps/rejected: -720.2745 |
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- Logps/chosen: -697.6023 |
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- Logits/rejected: 152.9660 |
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- Logits/chosen: 153.1356 |
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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: 8 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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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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- num_epochs: 2 |
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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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| 0.1424 | 1.8957 | 100 | 0.4722 | -0.0658 | -1.2673 | 0.7396 | 1.2015 | -720.2745 | -697.6023 | 152.9660 | 153.1356 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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