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README.md CHANGED
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- ---
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- license: bsl-1.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: openlm-research/open_llama_3b_v2
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+ model-index:
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+ - name: outputs/lora-out
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+ results: []
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+ ---
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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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+
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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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: openlm-research/open_llama_3b_v2
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+ model_type: LlamaForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ load_in_8bit: true
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+ load_in_4bit: false
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+ strict: false
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+ push_dataset_to_hub:
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+ datasets:
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+ - path: usagent100/newdataset
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+ type: alpaca
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+ dataset_prepared_path:
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+ val_set_size: 0.02
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+ adapter: lora
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+ lora_model_dir:
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+ sequence_len: 1024
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+ sample_packing: true
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+ lora_r: 8
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+ lora_alpha: 16
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+ lora_dropout: 0.0
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+ lora_target_modules:
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+ - gate_proj
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+ - down_proj
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+ - up_proj
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+ - q_proj
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+ - v_proj
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+ - k_proj
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+ - o_proj
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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_name:
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+ wandb_log_model:
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+ output_dir: ./outputs/lora-out
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+ gradient_accumulation_steps: 1
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+ micro_batch_size: 2
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+ num_epochs: 1
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+ optimizer: adamw_bnb_8bit
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+ torchdistx_path:
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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: false
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+ fp16: true
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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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+ gptq_groupsize:
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+ s2_attention:
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+ gptq_model_v1:
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+ warmup_steps: 20
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+ evals_per_epoch: 4
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+ saves_per_epoch: 1
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.1
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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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+ ```
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+
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+ </details><br>
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+
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+ # outputs/lora-out
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+
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+ This model is a fine-tuned version of [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0035
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - 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: 20
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+ - num_epochs: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 1.4292 | 0.0009 | 1 | 1.3002 |
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+ | 0.0001 | 0.25 | 277 | 0.0043 |
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+ | 0.0001 | 0.5 | 554 | 0.0036 |
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+ | 0.003 | 0.75 | 831 | 0.0034 |
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+ | 0.0038 | 1.0 | 1108 | 0.0035 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ "q_proj",
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+ "k_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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