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--- |
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base_model: data/zephyr-7b-sft-full-accumulation2 |
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tags: |
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- alignment-handbook |
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- trl |
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- dpo |
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- generated_from_trainer |
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- trl |
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- dpo |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: zephyr-7b-dpo-full-accumulation4 |
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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-accumulation4 |
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This model is a fine-tuned version of [data/zephyr-7b-sft-full-accumulation2](https://huggingface.co/data/zephyr-7b-sft-full-accumulation2) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5032 |
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- Rewards/chosen: -0.9893 |
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- Rewards/rejected: -2.0234 |
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- Rewards/accuracies: 0.7812 |
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- Rewards/margins: 1.0341 |
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- Logps/rejected: -462.7061 |
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- Logps/chosen: -358.6745 |
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- Logits/rejected: 3.3182 |
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- Logits/chosen: 2.7991 |
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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: 4 |
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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: 4 |
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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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| 0.59 | 0.2093 | 100 | 0.5946 | -0.2826 | -0.6651 | 0.7266 | 0.3825 | -326.8777 | -288.0025 | -2.2764 | -2.3187 | |
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| 0.5622 | 0.4186 | 200 | 0.5490 | -0.5914 | -1.2367 | 0.7578 | 0.6452 | -384.0357 | -318.8896 | -1.6885 | -1.7635 | |
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| 0.5069 | 0.6279 | 300 | 0.5186 | -0.9189 | -1.8568 | 0.7773 | 0.9379 | -446.0468 | -351.6352 | 3.7286 | 3.1924 | |
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| 0.5183 | 0.8373 | 400 | 0.5042 | -1.0384 | -2.0520 | 0.7773 | 1.0136 | -465.5701 | -363.5876 | 3.4727 | 2.9519 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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