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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: fine_tuning_codellama |
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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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[<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/chebbichafik133/sql-convert/runs/3q5mg1tl) |
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# fine_tuning_codellama |
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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: 0.1513 |
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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: 8 |
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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: 32 |
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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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| 1.1085 | 0.1010 | 20 | 1.0942 | |
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| 0.729 | 0.2020 | 40 | 0.5856 | |
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| 0.4941 | 0.3030 | 60 | 0.3775 | |
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| 0.2508 | 0.4040 | 80 | 0.2868 | |
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| 0.2139 | 0.5051 | 100 | 0.2528 | |
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| 0.2612 | 0.6061 | 120 | 0.2115 | |
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| 0.154 | 0.7071 | 140 | 0.2073 | |
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| 0.2558 | 0.8081 | 160 | 0.1936 | |
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| 0.1553 | 0.9091 | 180 | 0.1832 | |
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| 0.1831 | 1.0101 | 200 | 0.1872 | |
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| 0.2135 | 1.1111 | 220 | 0.1729 | |
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| 0.1278 | 1.2121 | 240 | 0.1724 | |
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| 0.21 | 1.3131 | 260 | 0.1676 | |
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| 0.1328 | 1.4141 | 280 | 0.1619 | |
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| 0.1731 | 1.5152 | 300 | 0.1651 | |
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| 0.1668 | 1.6162 | 320 | 0.1577 | |
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| 0.1259 | 1.7172 | 340 | 0.1565 | |
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| 0.191 | 1.8182 | 360 | 0.1543 | |
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| 0.129 | 1.9192 | 380 | 0.1515 | |
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| 0.1693 | 2.0202 | 400 | 0.1513 | |
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### Framework versions |
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- PEFT 0.6.0.dev0 |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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