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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-text2sql-ssh
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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/truskovskiyk/gpu-jobs-comparison/runs/cf8rtqag)
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+ # phi-3-text2sql-ssh
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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: 0.7745
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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: 4
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+ - total_train_batch_size: 16
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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: 1
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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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+ | No log | 0 | 0 | 2.8774 |
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+ | 1.3552 | 0.1072 | 500 | 0.8898 |
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+ | 0.8559 | 0.2143 | 1000 | 0.8311 |
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+ | 0.8152 | 0.3215 | 1500 | 0.8096 |
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+ | 0.7986 | 0.4287 | 2000 | 0.7940 |
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+ | 0.7901 | 0.5358 | 2500 | 0.7866 |
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+ | 0.7876 | 0.6430 | 3000 | 0.7806 |
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+ | 0.7806 | 0.7502 | 3500 | 0.7767 |
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+ | 0.7729 | 0.8574 | 4000 | 0.7751 |
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+ | 0.7735 | 0.9645 | 4500 | 0.7745 |
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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 4.42.3
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.19.1