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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: Qwen/Qwen2.5-7B-Instruct
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - ugaoo/medmcqa_lm_harness_10k_ts
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+ model-index:
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+ - name: out/Qwen_Qwen2.5_7B_Instruct_ugaoo_medmcqa_lm_harness_10k_ts
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.8.0.dev0`
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+ ```yaml
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+ base_model: Qwen/Qwen2.5-7B-Instruct
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+ trust_remote_code: true
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+
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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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+
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+ datasets:
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+ - path: ugaoo/medmcqa_lm_harness_10k_ts
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+ type: alpaca
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+ val_set_size: 0
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+ output_dir: ./out/Qwen_Qwen2.5_7B_Instruct_ugaoo_medmcqa_lm_harness_10k_ts
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+
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+ sequence_len: 4000
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ adapter: qlora
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+ lora_r: 256
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+ lora_alpha: 512
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+ lora_dropout: 0.05
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+ lora_target_linear: true
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+ lora_target_modules:
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+ - q_proj
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+ - k_proj
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+ - v_proj
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+ - o_proj
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+ - up_proj
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+ - down_proj
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+ - gate_proj
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+
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+ wandb_project: testsearch
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: Qwen_Qwen2.5_7B_Instruct_ugaoo_medmcqa_lm_harness_10k_ts
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 3
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+ micro_batch_size: 4
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+ num_epochs: 6
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+ optimizer: adamw_torch
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+ lr_scheduler: cosine
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+ learning_rate: 5e-6
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+
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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: false
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+
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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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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+
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+ warmup_steps: 100
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+ evals_per_epoch: 6
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+ eval_table_size:
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+ saves_per_epoch: 1
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.0
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+ fsdp:
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+ fsdp_config:
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+ save_total_limit: 6
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+ ```
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+
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+ </details><br>
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+
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+ # out/Qwen_Qwen2.5_7B_Instruct_ugaoo_medmcqa_lm_harness_10k_ts
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the ugaoo/medmcqa_lm_harness_10k_ts dataset.
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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: 5e-06
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - gradient_accumulation_steps: 3
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+ - total_train_batch_size: 12
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 6.0
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.49.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0