--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-0.5B tags: - axolotl - generated_from_trainer model-index: - name: ce0023fc-680c-4c8a-923d-ab948e707380 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora auto_find_batch_size: true base_model: Qwen/Qwen2.5-0.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - c77c45561ce0aa3f_train_data.json ds_type: json format: custom path: /workspace/input_data/c77c45561ce0aa3f_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null do_eval: true early_stopping_patience: 3 eval_max_new_tokens: 128 eval_steps: 50 evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: false group_by_length: true hub_model_id: lesso11/ce0023fc-680c-4c8a-923d-ab948e707380 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.000211 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 10 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_steps: 500 micro_batch_size: 4 mlflow_experiment_name: /tmp/c77c45561ce0aa3f_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null seed: 110 sequence_len: 512 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 4d0fabec-b916-4c39-b6e3-1963a602dd8c wandb_project: 11a wandb_run: your_name wandb_runid: 4d0fabec-b916-4c39-b6e3-1963a602dd8c warmup_steps: 50 weight_decay: 0.0 xformers_attention: null ```

# ce0023fc-680c-4c8a-923d-ab948e707380 This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.8689 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.000211 - train_batch_size: 4 - eval_batch_size: 4 - seed: 110 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 50 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0005 | 1 | 3.0528 | | 3.0983 | 0.0248 | 50 | 2.9541 | | 2.9496 | 0.0497 | 100 | 2.9590 | | 2.8879 | 0.0745 | 150 | 2.9211 | | 2.9325 | 0.0993 | 200 | 2.9027 | | 3.0635 | 0.1241 | 250 | 2.8898 | | 3.0316 | 0.1490 | 300 | 2.8787 | | 2.9748 | 0.1738 | 350 | 2.8720 | | 2.9601 | 0.1986 | 400 | 2.8702 | | 2.9456 | 0.2234 | 450 | 2.8675 | | 2.9716 | 0.2483 | 500 | 2.8689 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1