| --- |
| license: llama2 |
| base_model: codellama/CodeLlama-7b-hf |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: sql-code-llama |
| results: [] |
| library_name: peft |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # sql-code-llama |
|
|
| This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4577 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
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|
|
| The following `bitsandbytes` quantization config was used during training: |
| - quant_method: bitsandbytes |
| - _load_in_8bit: True |
| - _load_in_4bit: False |
| - llm_int8_threshold: 6.0 |
| - llm_int8_skip_modules: None |
| - llm_int8_enable_fp32_cpu_offload: False |
| - llm_int8_has_fp16_weight: False |
| - bnb_4bit_quant_type: fp4 |
| - bnb_4bit_use_double_quant: False |
| - bnb_4bit_compute_dtype: float32 |
| - bnb_4bit_quant_storage: uint8 |
| - load_in_4bit: False |
| - load_in_8bit: True |
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 400 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 2.1953 | 0.0465 | 20 | 2.0335 | |
| | 1.1292 | 0.0931 | 40 | 0.8342 | |
| | 0.8133 | 0.1396 | 60 | 0.6552 | |
| | 0.5873 | 0.1862 | 80 | 0.5861 | |
| | 0.4095 | 0.2327 | 100 | 0.5589 | |
| | 0.5731 | 0.2792 | 120 | 0.5159 | |
| | 0.4221 | 0.3258 | 140 | 0.5039 | |
| | 0.6365 | 0.3723 | 160 | 0.5159 | |
| | 0.4779 | 0.4188 | 180 | 0.4867 | |
| | 0.3584 | 0.4654 | 200 | 0.5007 | |
| | 0.5325 | 0.5119 | 220 | 0.4802 | |
| | 0.3998 | 0.5585 | 240 | 0.4767 | |
| | 0.5952 | 0.6050 | 260 | 0.4777 | |
| | 0.4649 | 0.6515 | 280 | 0.4671 | |
| | 0.3394 | 0.6981 | 300 | 0.4752 | |
| | 0.5084 | 0.7446 | 320 | 0.4669 | |
| | 0.3934 | 0.7912 | 340 | 0.4613 | |
| | 0.5762 | 0.8377 | 360 | 0.4617 | |
| | 0.4563 | 0.8842 | 380 | 0.4586 | |
| | 0.345 | 0.9308 | 400 | 0.4577 | |
|
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|
| ### Framework versions |
|
|
| - PEFT 0.6.0.dev0 |
| - Transformers 4.44.0.dev0 |
| - Pytorch 2.2.2+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
