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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: EvolCodeLlama-3.1-8B-Instruct |
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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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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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is_llama_derived_model: true |
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hub_model_id: EvolCodeLlama-3.1-8B-Instruct |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: mlabonne/Evol-Instruct-Python-1k |
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type: alpaca |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.02 |
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output_dir: ./qlora-out |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: axolotl |
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wandb_entity: |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 100 |
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eval_steps: 0.01 |
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save_strategy: epoch |
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save_steps: |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: "<|end_of_text|>" |
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``` |
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</details><br> |
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# EvolCodeLlama-3.1-8B-Instruct |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4057 |
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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: 4 |
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- total_train_batch_size: 8 |
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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_steps: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.388 | 0.0120 | 1 | 0.4443 | |
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| 0.3646 | 0.0359 | 3 | 0.4441 | |
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| 0.3216 | 0.0719 | 6 | 0.4439 | |
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| 0.3628 | 0.1078 | 9 | 0.4435 | |
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| 0.2506 | 0.1437 | 12 | 0.4417 | |
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| 0.2855 | 0.1796 | 15 | 0.4379 | |
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| 0.2472 | 0.2156 | 18 | 0.4310 | |
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| 0.3146 | 0.2515 | 21 | 0.4243 | |
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| 0.2829 | 0.2874 | 24 | 0.4185 | |
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| 0.2926 | 0.3234 | 27 | 0.4139 | |
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| 0.3832 | 0.3593 | 30 | 0.4099 | |
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| 0.3 | 0.3952 | 33 | 0.4069 | |
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| 0.2759 | 0.4311 | 36 | 0.4051 | |
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| 0.341 | 0.4671 | 39 | 0.4017 | |
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| 0.2268 | 0.5030 | 42 | 0.3989 | |
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| 0.3938 | 0.5389 | 45 | 0.3971 | |
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| 0.3478 | 0.5749 | 48 | 0.3951 | |
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| 0.2745 | 0.6108 | 51 | 0.3935 | |
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| 0.2623 | 0.6467 | 54 | 0.3920 | |
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| 0.3743 | 0.6826 | 57 | 0.3903 | |
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| 0.3205 | 0.7186 | 60 | 0.3898 | |
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| 0.332 | 0.7545 | 63 | 0.3897 | |
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| 0.268 | 0.7904 | 66 | 0.3876 | |
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| 0.2842 | 0.8263 | 69 | 0.3873 | |
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| 0.3677 | 0.8623 | 72 | 0.3868 | |
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| 0.212 | 0.8982 | 75 | 0.3857 | |
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| 0.2656 | 0.9341 | 78 | 0.3854 | |
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| 0.2499 | 0.9701 | 81 | 0.3844 | |
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| 0.3512 | 1.0060 | 84 | 0.3850 | |
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| 0.3069 | 1.0269 | 87 | 0.3848 | |
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| 0.3037 | 1.0629 | 90 | 0.3856 | |
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| 0.2785 | 1.0988 | 93 | 0.3864 | |
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| 0.206 | 1.1347 | 96 | 0.3873 | |
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| 0.3354 | 1.1707 | 99 | 0.3912 | |
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| 0.3281 | 1.2066 | 102 | 0.3882 | |
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| 0.3452 | 1.2425 | 105 | 0.3849 | |
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| 0.3153 | 1.2784 | 108 | 0.3851 | |
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| 0.3846 | 1.3144 | 111 | 0.3851 | |
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| 0.2847 | 1.3503 | 114 | 0.3842 | |
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| 0.3128 | 1.3862 | 117 | 0.3842 | |
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| 0.282 | 1.4222 | 120 | 0.3866 | |
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| 0.2186 | 1.4581 | 123 | 0.3876 | |
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| 0.2122 | 1.4940 | 126 | 0.3862 | |
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| 0.2877 | 1.5299 | 129 | 0.3837 | |
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| 0.2771 | 1.5659 | 132 | 0.3822 | |
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| 0.3518 | 1.6018 | 135 | 0.3820 | |
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| 0.302 | 1.6377 | 138 | 0.3829 | |
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| 0.2653 | 1.6737 | 141 | 0.3833 | |
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| 0.3281 | 1.7096 | 144 | 0.3832 | |
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| 0.2933 | 1.7455 | 147 | 0.3821 | |
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| 0.1959 | 1.7814 | 150 | 0.3824 | |
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| 0.2013 | 1.8174 | 153 | 0.3830 | |
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| 0.1909 | 1.8533 | 156 | 0.3824 | |
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| 0.2321 | 1.8892 | 159 | 0.3812 | |
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| 0.2695 | 1.9251 | 162 | 0.3798 | |
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| 0.2516 | 1.9611 | 165 | 0.3796 | |
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| 0.2148 | 1.9970 | 168 | 0.3796 | |
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| 0.2233 | 2.0180 | 171 | 0.3802 | |
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| 0.234 | 2.0539 | 174 | 0.3844 | |
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| 0.2615 | 2.0898 | 177 | 0.3938 | |
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| 0.1582 | 2.1257 | 180 | 0.4031 | |
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| 0.218 | 2.1617 | 183 | 0.4071 | |
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| 0.2438 | 2.1976 | 186 | 0.4072 | |
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| 0.1822 | 2.2335 | 189 | 0.4050 | |
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| 0.2163 | 2.2695 | 192 | 0.4028 | |
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| 0.1513 | 2.3054 | 195 | 0.4021 | |
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| 0.1898 | 2.3413 | 198 | 0.4031 | |
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| 0.1857 | 2.3772 | 201 | 0.4059 | |
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| 0.1909 | 2.4132 | 204 | 0.4075 | |
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| 0.1119 | 2.4491 | 207 | 0.4092 | |
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| 0.1794 | 2.4850 | 210 | 0.4091 | |
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| 0.1188 | 2.5210 | 213 | 0.4081 | |
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| 0.1525 | 2.5569 | 216 | 0.4073 | |
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| 0.1897 | 2.5928 | 219 | 0.4069 | |
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| 0.1785 | 2.6287 | 222 | 0.4064 | |
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| 0.169 | 2.6647 | 225 | 0.4064 | |
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| 0.1518 | 2.7006 | 228 | 0.4060 | |
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| 0.1896 | 2.7365 | 231 | 0.4052 | |
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| 0.1675 | 2.7725 | 234 | 0.4055 | |
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| 0.2193 | 2.8084 | 237 | 0.4055 | |
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| 0.1887 | 2.8443 | 240 | 0.4057 | |
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| 0.1639 | 2.8802 | 243 | 0.4055 | |
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| 0.1701 | 2.9162 | 246 | 0.4058 | |
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| 0.2019 | 2.9521 | 249 | 0.4057 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
