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--- |
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library_name: peft |
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license: mit |
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base_model: microsoft/Phi-3-mini-128k-instruct |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: phi-3-mini-sft-indicqa-hindi-v0.1 |
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results: [] |
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datasets: |
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- sepiatone/ai4bharat-IndicQA-hi-202410 |
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- ai4bharat/IndicQA |
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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-3-mini-sft-indicqa-hindi-v0.1** |
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### model description |
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this model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the dataset [ |
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ai4bharat-IndicQA-hi-202410](https://huggingface.co/datasets/sepiatone/ai4bharat-IndicQA-hi-202410). |
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prepared by [@sepiatone](https://github.com/sepiatone). |
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### intended uses & limitations |
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intended for an educational and non-commercial purpose. |
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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: 0.0002 |
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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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- 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: 0.03 |
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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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#### library versions |
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- PEFT 0.13.2 |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
