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--- |
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license: apache-2.0 |
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base_model: microsoft/phi-2 |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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--- |
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# outputs |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) using [SPIN](https://github.com/uclaml/SPIN) on [ultrachat_200k dataset](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k). |
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# What's new |
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I think SPIN not only can use on a SFT model, but also it can use on a pretrained model. |
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Therefore, I use SPIN on a pretrained model microsoft/phi-2. And I get a higher score better than origin pretrained model. You can check the [open llm leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). |
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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: 1 |
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- eval_batch_size: 1 |
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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: 64 |
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- total_eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
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