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--- |
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license: mit |
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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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base_model: microsoft/phi-2 |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: phi-2-gpo-renew2-b0.001-vllm-i1 |
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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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# phi-2-gpo-renew2-b0.001-vllm-i1 |
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This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-renew2-b0.001-i0](https://huggingface.co/DUAL-GPO/phi-2-gpo-renew2-b0.001-i0) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0674 |
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- Rewards/chosen: 0.2141 |
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- Rewards/rejected: 0.1823 |
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- Rewards/accuracies: 0.5025 |
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- Rewards/margins: 0.0317 |
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- Logps/rejected: -1694.0739 |
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- Logps/chosen: -2002.3224 |
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- Logits/rejected: 0.1179 |
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- Logits/chosen: 0.1215 |
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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: 4 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_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: 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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| 0.1015 | 0.16 | 100 | 0.0587 | 0.1574 | 0.1353 | 0.5010 | 0.0221 | -1741.1520 | -2059.0308 | -0.0782 | -0.0740 | |
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| 0.1063 | 0.32 | 200 | 0.0662 | 0.2082 | 0.1782 | 0.5035 | 0.0300 | -1698.2368 | -2008.2380 | 0.0246 | 0.0308 | |
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| 0.089 | 0.48 | 300 | 0.0674 | 0.2080 | 0.1779 | 0.5025 | 0.0302 | -1698.5458 | -2008.3832 | 0.1068 | 0.1094 | |
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| 0.0836 | 0.64 | 400 | 0.0678 | 0.2130 | 0.1815 | 0.5045 | 0.0315 | -1694.8785 | -2003.3719 | 0.0938 | 0.0992 | |
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| 0.0823 | 0.8 | 500 | 0.0675 | 0.2147 | 0.1828 | 0.5030 | 0.0319 | -1693.5775 | -2001.7003 | 0.1134 | 0.1173 | |
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| 0.095 | 0.96 | 600 | 0.0674 | 0.2143 | 0.1825 | 0.5025 | 0.0318 | -1693.8877 | -2002.1124 | 0.1193 | 0.1230 | |
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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 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
