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--- |
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license: llama2 |
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base_model: codellama/CodeLlama-7b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: sql-code-llama |
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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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# sql-code-llama |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0810 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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_steps: 100 |
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- training_steps: 400 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.033 | 0.28 | 20 | 1.9418 | |
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| 1.3136 | 0.56 | 40 | 0.8477 | |
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| 0.1674 | 0.83 | 60 | 0.1384 | |
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| 0.1276 | 1.11 | 80 | 0.1220 | |
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| 0.1106 | 1.39 | 100 | 0.1046 | |
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| 0.102 | 1.67 | 120 | 0.0946 | |
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| 0.0917 | 1.94 | 140 | 0.0903 | |
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| 0.0895 | 2.22 | 160 | 0.0887 | |
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| 0.0889 | 2.5 | 180 | 0.0872 | |
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| 0.0874 | 2.78 | 200 | 0.0858 | |
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| 0.086 | 3.06 | 220 | 0.0851 | |
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| 0.0861 | 3.33 | 240 | 0.0842 | |
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| 0.085 | 3.61 | 260 | 0.0835 | |
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| 0.0821 | 3.89 | 280 | 0.0830 | |
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| 0.0838 | 4.17 | 300 | 0.0823 | |
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| 0.0816 | 4.44 | 320 | 0.0820 | |
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| 0.0785 | 4.72 | 340 | 0.0815 | |
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| 0.0819 | 5.0 | 360 | 0.0812 | |
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| 0.081 | 5.28 | 380 | 0.0810 | |
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| 0.0765 | 5.56 | 400 | 0.0810 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.15.0 |
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