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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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base_model: microsoft/phi-1_5 |
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datasets: |
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- Ritvik19/open-hermes-2_5-reformatted |
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model-index: |
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- name: openhermes-phi-1_5-sft-qlora |
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results: [] |
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--- |
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**Note**: This model card has been generated automatically according to the information the Trainer had access to. |
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Visit the [model card](https://ritvik19.github.io/small-llms/) to see the full description. |
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# openhermes-phi-1_5-sft-qlora |
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This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the Ritvik19/open-hermes-2_5-reformatted dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4192 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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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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- gradient_accumulation_steps: 128 |
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- total_train_batch_size: 128 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.3662 | 0.9994 | 1559 | 1.4192 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.1 |
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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 |
