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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: karim_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/llm_project/llm_project-org/runs/nb0hywqq) |
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# karim_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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1887 |
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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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| 1.146 | 0.0787 | 20 | 1.2504 | |
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| 0.8176 | 0.1573 | 40 | 0.6454 | |
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| 0.6291 | 0.2360 | 60 | 0.4881 | |
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| 0.3068 | 0.3147 | 80 | 0.3589 | |
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| 0.5266 | 0.3933 | 100 | 0.4066 | |
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| 0.302 | 0.4720 | 120 | 0.2728 | |
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| 0.1989 | 0.5506 | 140 | 0.2604 | |
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| 0.3157 | 0.6293 | 160 | 0.2502 | |
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| 0.1768 | 0.7080 | 180 | 0.2285 | |
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| 0.4553 | 0.7866 | 200 | 0.2575 | |
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| 0.2183 | 0.8653 | 220 | 0.2152 | |
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| 0.1815 | 0.9440 | 240 | 0.2148 | |
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| 0.2704 | 1.0226 | 260 | 0.2142 | |
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| 0.1662 | 1.1013 | 280 | 0.2001 | |
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| 0.3306 | 1.1799 | 300 | 0.2065 | |
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| 0.2161 | 1.2586 | 320 | 0.1967 | |
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| 0.1429 | 1.3373 | 340 | 0.1925 | |
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| 0.2892 | 1.4159 | 360 | 0.1927 | |
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| 0.1459 | 1.4946 | 380 | 0.1894 | |
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| 0.3078 | 1.5733 | 400 | 0.1887 | |
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### Framework versions |
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- PEFT 0.6.0.dev0 |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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