| # Llama-2-13b SuperCOT lora checkpoints | |
| These are my 2nd round of Llama-2-13b SuperCOT Lora checkpoints trained using QLora on the [SuperCOT Dataset](https://huggingface.co/datasets/kaiokendev/SuperCOT-dataset) with different parameters closer to the llama 1 supercot. | |
| ### Architecture | |
| - **Model Architecture**: Llama-2-13b | |
| - **Training Algorithm**: QLora | |
| ### Training Details | |
| - **Dataset**: [SuperCOT Dataset](https://huggingface.co/datasets/kaiokendev/SuperCOT-dataset) | |
| - **Datset type**: alpaca | |
| - **Training Parameters**: [See Here](https://github.com/OpenAccess-AI-Collective/axolotl/blob/main/examples/llama-2/qlora.yml) | |
| - **Training Environment**: Axolotl | |
| - **sequence_len**: 4096 | |
| ### Uploads/merges | |
| Thanks to these gigachads for uploading | |
| - [llama2 13B GGUF by Peepy](https://huggingface.co/Peeepy/SuperCOT-L2-13B-GGUF) | |
| - [llama2 13B GPTQ by Peepy](https://huggingface.co/Peeepy/SuperCOT-L2-13B-GPTQ) | |
| ### yml | |
| ``` | |
| base_model: NousResearch/Llama-2-13b-hf | |
| base_model_config: NousResearch/Llama-2-13b-hf | |
| model_type: LlamaForCausalLM | |
| tokenizer_type: LlamaTokenizer | |
| is_llama_derived_model: true | |
| load_in_8bit: false | |
| load_in_4bit: true | |
| strict: false | |
| datasets: | |
| path: kaiokendev/SuperCOT-dataset | |
| type: alpaca | |
| dataset_prepared_path: last_run_prepared | |
| val_set_size: 0.01 | |
| output_dir: ./qlora-out/checkpoint-4230 | |
| adapter: qlora | |
| lora_model_dir: | |
| sequence_len: 4096 | |
| sample_packing: true | |
| pad_to_sequence_len: true | |
| lora_r: 8 | |
| lora_alpha: 16 | |
| lora_dropout: 0 | |
| lora_target_modules: | |
| lora_target_linear: true | |
| lora_fan_in_fan_out: | |
| wandb_project: | |
| wandb_entity: | |
| wandb_watch: | |
| wandb_run_id: | |
| wandb_log_model: | |
| gradient_accumulation_steps: 2 | |
| micro_batch_size: 1 | |
| num_epochs: 3 | |
| optimizer: paged_adamw_32bit | |
| lr_scheduler: cosine | |
| learning_rate: 0.0003 | |
| train_on_inputs: false | |
| group_by_length: false | |
| bf16: true | |
| fp16: false | |
| tf32: false | |
| gradient_checkpointing: true | |
| early_stopping_patience: | |
| resume_from_checkpoint: | |
| local_rank: | |
| logging_steps: 1 | |
| xformers_attention: | |
| flash_attention: true | |
| warmup_steps: 10 | |
| eval_steps: 20 | |
| save_steps: | |
| debug: | |
| deepspeed: | |
| weight_decay: 0.0 | |
| fsdp: | |
| fsdp_config: | |
| special_tokens: | |
| bos_token: "<s>" | |
| eos_token: "</s>" | |
| unk_token: "<unk>" | |
| ``` | |
| ## Acknowledgments | |
| Special thanks to the creators of the datasets in SuperCOT. Additionally, thanks to Kaiokendev for curating the SuperCOT dataset. Thanks to the contributors of the Axolotl. | |
| ## Stuff generated from axolotl: | |
| --- | |
| library_name: peft | |
| --- | |
| ## Training procedure | |
| The following `bitsandbytes` quantization config was used during training: | |
| - quant_method: bitsandbytes | |
| - load_in_8bit: False | |
| - load_in_4bit: True | |
| - llm_int8_threshold: 6.0 | |
| - llm_int8_skip_modules: None | |
| - llm_int8_enable_fp32_cpu_offload: False | |
| - llm_int8_has_fp16_weight: False | |
| - bnb_4bit_quant_type: nf4 | |
| - bnb_4bit_use_double_quant: True | |
| - bnb_4bit_compute_dtype: bfloat16 | |
| ### Framework versions | |
| - PEFT 0.6.0.dev0 | |