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--- |
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license: llama2 |
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library_name: peft |
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tags: |
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- axolotl |
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- generated_from_trainer |
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base_model: codellama/CodeLlama-7b-hf |
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model-index: |
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- name: EvilCodeLlama-7b |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.3.0` |
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```yaml |
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base_model: codellama/CodeLlama-7b-hf |
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base_model_config: codellama/CodeLlama-7b-hf |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_llama_derived_model: true |
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hub_model_id: EvilCodeLlama-7b |
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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: dhuynh95/Magicoder-Evol-Instruct-110K-Filtered_0.35 |
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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-evil-codellama |
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adapter: qlora |
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lora_model_dir: |
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eval_sample_packing: false |
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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: 16 |
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num_epochs: 1 |
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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: true |
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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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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# EvilCodeLlama-7b |
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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: 1.1701 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.2543 | 0.04 | 1 | 1.2447 | |
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| 1.2781 | 0.08 | 2 | 1.2445 | |
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| 1.2677 | 0.12 | 3 | 1.2446 | |
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| 1.2725 | 0.16 | 4 | 1.2447 | |
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| 1.2704 | 0.21 | 5 | 1.2440 | |
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| 1.2572 | 0.25 | 6 | 1.2442 | |
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| 1.2875 | 0.29 | 7 | 1.2439 | |
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| 1.2672 | 0.33 | 8 | 1.2434 | |
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| 1.2601 | 0.37 | 9 | 1.2430 | |
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| 1.2808 | 0.41 | 10 | 1.2421 | |
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| 1.2665 | 0.45 | 11 | 1.2411 | |
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| 1.2572 | 0.49 | 12 | 1.2400 | |
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| 1.2505 | 0.54 | 13 | 1.2384 | |
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| 1.264 | 0.58 | 14 | 1.2365 | |
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| 1.2809 | 0.62 | 15 | 1.2338 | |
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| 1.2054 | 0.66 | 16 | 1.2308 | |
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| 1.2732 | 0.7 | 17 | 1.2269 | |
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| 1.2586 | 0.74 | 18 | 1.2219 | |
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| 1.2939 | 0.78 | 19 | 1.2161 | |
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| 1.2713 | 0.82 | 20 | 1.2086 | |
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| 1.2154 | 0.87 | 21 | 1.2008 | |
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| 1.213 | 0.91 | 22 | 1.1917 | |
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| 1.2183 | 0.95 | 23 | 1.1813 | |
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| 1.1594 | 0.99 | 24 | 1.1701 | |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
