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HuggingFaceUser/adapter-medmobile-MEDQA-Extended-V2

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README.md ADDED
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+ ---
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+ base_model: microsoft/Phi-3-mini-4k-instruct
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+ library_name: peft
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+ license: mit
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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-LoRA-MEDQA-Extended-V2
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+ results: []
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+ ---
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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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+
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+ # phi-3-mini-LoRA-MEDQA-Extended-V2
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+
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+ This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6514
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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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: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.7812 | 0.2205 | 100 | 0.6947 |
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+ | 0.6795 | 0.4410 | 200 | 0.6694 |
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+ | 0.6686 | 0.6615 | 300 | 0.6633 |
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+ | 0.662 | 0.8820 | 400 | 0.6597 |
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+ | 0.6603 | 1.1025 | 500 | 0.6578 |
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+ | 0.6586 | 1.3230 | 600 | 0.6566 |
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+ | 0.6538 | 1.5436 | 700 | 0.6552 |
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+ | 0.6551 | 1.7641 | 800 | 0.6539 |
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+ | 0.6542 | 1.9846 | 900 | 0.6535 |
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+ | 0.65 | 2.2051 | 1000 | 0.6525 |
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+ | 0.6522 | 2.4256 | 1100 | 0.6519 |
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+ | 0.6526 | 2.6461 | 1200 | 0.6515 |
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+ | 0.6501 | 2.8666 | 1300 | 0.6514 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.43.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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