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README.md
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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-sagemaker
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results: []
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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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[<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/uwp42gjd)
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# phi-3-text2sql-sagemaker
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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: 0.7747
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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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: 0.0001
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0 | 0 | 2.8740 |
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| 1.3554 | 0.1072 | 500 | 0.8899 |
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| 0.8559 | 0.2143 | 1000 | 0.8313 |
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| 0.8154 | 0.3215 | 1500 | 0.8094 |
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| 0.7986 | 0.4287 | 2000 | 0.7940 |
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| 0.79 | 0.5358 | 2500 | 0.7870 |
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| 0.7877 | 0.6430 | 3000 | 0.7806 |
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| 0.7806 | 0.7502 | 3500 | 0.7769 |
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| 0.773 | 0.8574 | 4000 | 0.7752 |
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| 0.7737 | 0.9645 | 4500 | 0.7747 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.42.3
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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