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--- |
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license: mit |
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base_model: HuggingFaceH4/mistral-7b-sft-beta |
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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-dpo-full |
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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-full |
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This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0069 |
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- Rewards/chosen: -2.6575 |
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- Rewards/rejected: -5.6311 |
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- Rewards/accuracies: 0.6914 |
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- Rewards/margins: 2.9735 |
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- Logps/rejected: -820.4592 |
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- Logps/chosen: -522.7909 |
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- Logits/rejected: -2.4988 |
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- Logits/chosen: -2.5238 |
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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: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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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: 1 |
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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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| 0.0071 | 0.21 | 100 | 0.0072 | -0.8922 | -1.6083 | 0.6523 | 0.7161 | -418.1843 | -346.2603 | -2.6342 | -2.6489 | |
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| 0.0068 | 0.42 | 200 | 0.0070 | -1.7394 | -3.1970 | 0.6680 | 1.4577 | -577.0542 | -430.9749 | -2.6058 | -2.6219 | |
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| 0.0069 | 0.63 | 300 | 0.0069 | -2.2358 | -4.6352 | 0.6992 | 2.3994 | -720.8748 | -480.6185 | -2.5115 | -2.5351 | |
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| 0.0067 | 0.84 | 400 | 0.0069 | -2.6575 | -5.6311 | 0.6914 | 2.9735 | -820.4592 | -522.7909 | -2.4988 | -2.5238 | |
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### Framework versions |
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- Transformers 4.35.2 |
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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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