--- library_name: peft base_model: katuni4ka/tiny-random-qwen1.5-moe tags: - axolotl - generated_from_trainer model-index: - name: 7ba33cf8-f43e-4b02-af41-9b601eeaee87 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: katuni4ka/tiny-random-qwen1.5-moe bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 18a5afee19d07bd3_train_data.json ds_type: json format: custom path: /workspace/input_data/18a5afee19d07bd3_train_data.json type: field_input: captions field_instruction: ASR field_output: whole_caption 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: lesso10/7ba33cf8-f43e-4b02-af41-9b601eeaee87 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.00021 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/18a5afee19d07bd3_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: 100 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: 19d65acb-908a-4ff2-b1f6-0eb0b9d338a3 wandb_project: 10a wandb_run: your_name wandb_runid: 19d65acb-908a-4ff2-b1f6-0eb0b9d338a3 warmup_steps: 50 weight_decay: 0.0 xformers_attention: null ```

# 7ba33cf8-f43e-4b02-af41-9b601eeaee87 This model is a fine-tuned version of [katuni4ka/tiny-random-qwen1.5-moe](https://huggingface.co/katuni4ka/tiny-random-qwen1.5-moe) on the None dataset. It achieves the following results on the evaluation set: - Loss: 11.8158 ## 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: 0.00021 - train_batch_size: 4 - eval_batch_size: 4 - seed: 100 - 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 | 0.0000 | 1 | 11.9326 | | 11.88 | 0.0016 | 50 | 11.8662 | | 11.8447 | 0.0032 | 100 | 11.8449 | | 11.8328 | 0.0048 | 150 | 11.8347 | | 11.8245 | 0.0064 | 200 | 11.8269 | | 11.8205 | 0.0081 | 250 | 11.8222 | | 11.8158 | 0.0097 | 300 | 11.8195 | | 11.8144 | 0.0113 | 350 | 11.8171 | | 11.8131 | 0.0129 | 400 | 11.8162 | | 11.8134 | 0.0145 | 450 | 11.8158 | | 11.8119 | 0.0161 | 500 | 11.8158 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1