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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: camel-lora |
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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: `0.4.0` |
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```yaml |
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base_model: codellama/CodeLlama-7b-hf |
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model_type: LlamaForCausalLM |
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tokenizer_type: CodeLlamaTokenizer |
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is_llama_derived_model: true |
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hub_model_id: noeloco/camel-lora |
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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: noeloco/fizzbuzz-sft |
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type: alpaca |
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ds_type: json |
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hf_use_auth_token: true |
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push_dataset_to_hub: noeloco |
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val_set_size: 0.05 |
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output_dir: ./lora-out |
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chat_template: chatml |
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sequence_len: 4096 |
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sample_packing: false |
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pad_to_sequence_len: true |
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adapter: qlora |
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lora_model_dir: |
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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_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: runpod1 |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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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: 4 |
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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: auto |
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fp16: false |
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tf32: true |
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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: 10 |
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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: true |
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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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# camel-lora |
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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: 0.0290 |
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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: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.7685 | 0.06 | 1 | 2.5524 | |
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| 1.8762 | 0.29 | 5 | 2.4927 | |
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| 1.215 | 0.57 | 10 | 1.4546 | |
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| 0.484 | 0.86 | 15 | 0.7250 | |
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| 0.3667 | 1.14 | 20 | 0.4146 | |
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| 0.1638 | 1.43 | 25 | 0.2123 | |
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| 0.2948 | 1.71 | 30 | 0.0980 | |
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| 0.2003 | 2.0 | 35 | 0.0629 | |
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| 0.0888 | 2.29 | 40 | 0.0577 | |
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| 0.0918 | 2.57 | 45 | 0.0414 | |
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| 0.0931 | 2.86 | 50 | 0.0363 | |
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| 0.0982 | 3.14 | 55 | 0.0304 | |
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| 0.0849 | 3.43 | 60 | 0.0289 | |
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| 0.0511 | 3.71 | 65 | 0.0290 | |
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### Framework versions |
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- PEFT 0.10.1.dev0 |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |