--- library_name: peft license: other base_model: Qwen/Qwen1.5-0.5B-Chat tags: - axolotl - generated_from_trainer model-index: - name: d21bbf89-cbba-4dd5-b72d-665029f9b65f results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-0.5B-Chat bf16: true chat_template: llama3 datasets: - data_files: - 918bd6561dce8e76_train_data.json ds_type: json format: custom path: /workspace/input_data/918bd6561dce8e76_train_data.json type: field_input: literal_translation field_instruction: language field_output: prompt format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: false group_by_length: false hub_model_id: lesso12/d21bbf89-cbba-4dd5-b72d-665029f9b65f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/918bd6561dce8e76_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: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: bd4284bb-9f00-44a3-90cd-66bb32d39100 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: bd4284bb-9f00-44a3-90cd-66bb32d39100 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# d21bbf89-cbba-4dd5-b72d-665029f9b65f This model is a fine-tuned version of [Qwen/Qwen1.5-0.5B-Chat](https://huggingface.co/Qwen/Qwen1.5-0.5B-Chat) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.6863 ## 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: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - 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: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 5.8593 | 0.0006 | 1 | 5.0062 | | 2.8746 | 0.0029 | 5 | 4.7272 | | 2.8893 | 0.0058 | 10 | 3.9926 | | 2.7348 | 0.0087 | 15 | 3.8252 | | 3.3659 | 0.0117 | 20 | 3.7121 | | 4.8594 | 0.0146 | 25 | 3.6863 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1