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--- |
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license: llama2 |
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library_name: peft |
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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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base_model: codellama/CodeLlama-7b-hf |
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model-index: |
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- name: codellama-7b-text-to-sql |
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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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# codellama-7b-text-to-sql |
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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: 0.4224 |
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- Rouge Scores: {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704} |
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- Bleu Scores: [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271] |
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- Gen Len: 138.6233 |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge Scores | Bleu Scores | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:| |
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| 0.4229 | 1.0 | 4800 | 0.4162 | {'rouge1': 0.9506510098188024, 'rouge2': 0.8949972495187106, 'rougeL': 0.9142255494550289, 'rougeLsum': 0.9506551339456668} | [0.9637759028147137, 0.9546609970402782, 0.9437656479747901, 0.9323669423057117] | 138.6233 | |
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| 0.3314 | 2.0 | 9600 | 0.4004 | {'rouge1': 0.9524326989909003, 'rouge2': 0.8987509624898048, 'rougeL': 0.9179414410323365, 'rougeLsum': 0.9524550499725172} | [0.9652102001679345, 0.9563139443363083, 0.9456856232691524, 0.9345677892198804] | 138.6233 | |
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| 0.2666 | 3.0 | 14400 | 0.4224 | {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704} | [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271] | 138.6233 | |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
