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# Llama-2-13b SuperCOT lora checkpoints |
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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. |
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### Architecture |
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- **Model Architecture**: Llama-2-13b |
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- **Training Algorithm**: QLora |
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### Training Details |
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- **Dataset**: [SuperCOT Dataset](https://huggingface.co/datasets/kaiokendev/SuperCOT-dataset) |
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- **Datset type**: alpaca |
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- **Training Parameters**: [See Here](https://github.com/OpenAccess-AI-Collective/axolotl/blob/main/examples/llama-2/qlora.yml) |
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- **Training Environment**: Axolotl |
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- **sequence_len**: 4096 |
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### Uploads/merges |
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Thanks to these gigachads for uploading |
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- [llama2 13B GGUF by Peepy](https://huggingface.co/Peeepy/SuperCOT-L2-13B-GGUF) |
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- [llama2 13B GPTQ by Peepy](https://huggingface.co/Peeepy/SuperCOT-L2-13B-GPTQ) |
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### yml |
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``` |
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base_model: NousResearch/Llama-2-13b-hf |
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base_model_config: NousResearch/Llama-2-13b-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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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: kaiokendev/SuperCOT-dataset |
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type: alpaca |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.01 |
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output_dir: ./qlora-out/checkpoint-4230 |
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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: true |
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pad_to_sequence_len: true |
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lora_r: 8 |
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lora_alpha: 16 |
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lora_dropout: 0 |
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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: |
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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: 2 |
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micro_batch_size: 1 |
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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: 0.0003 |
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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: 10 |
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eval_steps: 20 |
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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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## Acknowledgments |
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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. |
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## Stuff generated from axolotl: |
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--- |
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library_name: peft |
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--- |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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### Framework versions |
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- PEFT 0.6.0.dev0 |
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