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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- alignment-handbook |
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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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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: zephyr-7b-gpo-iter2 |
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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-gpo-iter2 |
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This model is a fine-tuned version of [DUAL-GPO/zephyr-7b-gpo-iter1](https://huggingface.co/DUAL-GPO/zephyr-7b-gpo-iter1) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0114 |
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- Rewards/chosen: -0.0874 |
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- Rewards/rejected: -0.0645 |
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- Rewards/accuracies: 0.3940 |
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- Rewards/margins: -0.0229 |
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- Logps/rejected: -264.6114 |
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- Logps/chosen: -288.2511 |
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- Logits/rejected: -2.1907 |
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- Logits/chosen: -2.3882 |
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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-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 2 |
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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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| 0.0012 | 0.3 | 100 | 0.0016 | -0.0164 | -0.0160 | 0.5035 | -0.0005 | -259.7555 | -281.1500 | -2.1644 | -2.3583 | |
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| 0.0011 | 0.61 | 200 | 0.0018 | -0.0088 | -0.0077 | 0.4815 | -0.0011 | -258.9317 | -280.3858 | -2.1837 | -2.3781 | |
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| 0.0015 | 0.91 | 300 | 0.0019 | -0.0167 | -0.0149 | 0.4805 | -0.0017 | -259.6521 | -281.1740 | -2.1796 | -2.3740 | |
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| 0.0397 | 1.22 | 400 | 0.0074 | -0.0779 | -0.0627 | 0.4160 | -0.0151 | -264.4323 | -287.2935 | -2.1632 | -2.3568 | |
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| 0.0305 | 1.52 | 500 | 0.0117 | -0.0898 | -0.0668 | 0.3945 | -0.0230 | -264.8388 | -288.4842 | -2.1902 | -2.3875 | |
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| 0.0366 | 1.82 | 600 | 0.0115 | -0.0876 | -0.0647 | 0.4000 | -0.0230 | -264.6301 | -288.2723 | -2.1900 | -2.3873 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
