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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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<!-- 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/cf8rtqag) |
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# phi-3-text2sql-ssh |
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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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## 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 | 2.8774 | |
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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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### Framework versions |
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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 |
