--- library_name: peft tags: - generated_from_trainer base_model: jamba model-index: - name: out results: [] --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config axolotl version: `0.4.0` ```yaml base_model: jamba trust_remote_code: true load_in_8bit: false load_in_4bit: true strict: false datasets: - path: scikit_admin_result.json ds_type: json type: sharegpt conversation: chatml dataset_prepared_path: val_set_size: 0.01 output_dir: ./out sequence_len: 6000 sample_packing: true pad_to_sequence_len: false eval_sample_packing: true use_wandb: false adapter: qlora lora_r: 8 lora_alpha: 16 lora_dropout: 0.05 lora_target_linear: true low_cpu_mem_usage: true gradient_accumulation_steps: 4 micro_batch_size: 1 num_epochs: 2 optimizer: paged_adamw_8bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: false early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 10 evals_per_epoch: 2 saves_per_epoch: 2 debug: weight_decay: 0.0 special_tokens: ```

# out This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2356 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.4337 | 0.0 | 1 | 0.3783 | | 0.2537 | 0.5 | 103 | 0.2345 | | 0.2161 | 1.0 | 206 | 0.2258 | | 0.1821 | 1.47 | 309 | 0.2356 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.0