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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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library_name: peft |
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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: 0.4577 |
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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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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- _load_in_8bit: True |
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- _load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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- bnb_4bit_quant_storage: uint8 |
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- load_in_4bit: False |
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- load_in_8bit: True |
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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: 32 |
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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: 128 |
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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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| 2.1953 | 0.0465 | 20 | 2.0335 | |
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| 1.1292 | 0.0931 | 40 | 0.8342 | |
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| 0.8133 | 0.1396 | 60 | 0.6552 | |
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| 0.5873 | 0.1862 | 80 | 0.5861 | |
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| 0.4095 | 0.2327 | 100 | 0.5589 | |
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| 0.5731 | 0.2792 | 120 | 0.5159 | |
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| 0.4221 | 0.3258 | 140 | 0.5039 | |
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| 0.6365 | 0.3723 | 160 | 0.5159 | |
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| 0.4779 | 0.4188 | 180 | 0.4867 | |
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| 0.3584 | 0.4654 | 200 | 0.5007 | |
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| 0.5325 | 0.5119 | 220 | 0.4802 | |
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| 0.3998 | 0.5585 | 240 | 0.4767 | |
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| 0.5952 | 0.6050 | 260 | 0.4777 | |
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| 0.4649 | 0.6515 | 280 | 0.4671 | |
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| 0.3394 | 0.6981 | 300 | 0.4752 | |
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| 0.5084 | 0.7446 | 320 | 0.4669 | |
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| 0.3934 | 0.7912 | 340 | 0.4613 | |
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| 0.5762 | 0.8377 | 360 | 0.4617 | |
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| 0.4563 | 0.8842 | 380 | 0.4586 | |
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| 0.345 | 0.9308 | 400 | 0.4577 | |
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### Framework versions |
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- PEFT 0.6.0.dev0 |
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- Transformers 4.44.0.dev0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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