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fullmetaldr/ft-phi-3

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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
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/caballeromarco-microsoft/Phi3-mini-ft-python-code/runs/5en76rqc)
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+ # phi-3-mini-LoRA
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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: 0.5562
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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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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+ | 0.8876 | 0.1810 | 100 | 0.6187 |
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+ | 0.5945 | 0.3619 | 200 | 0.5746 |
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+ | 0.57 | 0.5429 | 300 | 0.5678 |
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+ | 0.5714 | 0.7238 | 400 | 0.5638 |
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+ | 0.558 | 0.9048 | 500 | 0.5623 |
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+ | 0.5654 | 1.0857 | 600 | 0.5608 |
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+ | 0.5526 | 1.2667 | 700 | 0.5597 |
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+ | 0.5538 | 1.4476 | 800 | 0.5588 |
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+ | 0.5667 | 1.6286 | 900 | 0.5579 |
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+ | 0.5557 | 1.8095 | 1000 | 0.5574 |
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+ | 0.5546 | 1.9905 | 1100 | 0.5570 |
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+ | 0.5469 | 2.1715 | 1200 | 0.5566 |
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+ | 0.5611 | 2.3524 | 1300 | 0.5566 |
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+ | 0.5511 | 2.5334 | 1400 | 0.5563 |
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+ | 0.5523 | 2.7143 | 1500 | 0.5562 |
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+ | 0.5541 | 2.8953 | 1600 | 0.5562 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.42.4
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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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