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--- |
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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: NousResearch/Llama-2-7b-hf |
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model-index: |
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- name: neocortex |
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results: [] |
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--- |
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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: NousResearch/Llama-2-7b-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: neocortex |
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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: SethGA/neocortex |
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type: alpaca |
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shards: 20 |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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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: 4096 |
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sample_packing: false |
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eval_sample_packing: false |
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pad_to_sequence_len: 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: neocortex |
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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: checkpoint |
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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: auto |
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fp16: |
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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: 10 |
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eval_steps: 20 |
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eval_table_size: 5 |
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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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# neocortex |
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This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the [neocortex_23k](https://huggingface.co/datasets/SethGA/neocortex_23k) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4558 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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: 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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| 1.5181 | 0.29 | 20 | 1.5627 | |
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| 1.437 | 0.58 | 40 | 1.4861 | |
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| 1.5196 | 0.87 | 60 | 1.4610 | |
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| 1.4037 | 1.16 | 80 | 1.4512 | |
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| 1.372 | 1.45 | 100 | 1.4493 | |
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| 1.3853 | 1.74 | 120 | 1.4424 | |
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| 1.2367 | 2.03 | 140 | 1.4460 | |
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| 1.283 | 2.32 | 160 | 1.4602 | |
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| 1.2933 | 2.61 | 180 | 1.4583 | |
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| 1.2397 | 2.9 | 200 | 1.4558 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.0 |
