--- license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T tags: - generated_from_trainer model-index: - name: TinyLlama-Tinybook-epochs-1-lr-0002_Train_On_Input results: [] --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config axolotl version: `0.4.0` ```yaml adapter: null base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T bf16: auto dataset_prepared_path: last_run_prepared datasets: - path: utrgvseniorproject/Tinybook type: completion debug: null deepspeed: null early_stopping_patience: null eval_sample_packing: false eval_table_size: null evals_per_epoch: 4 flash_attention: true flash_attn_cross_entropy: false flash_attn_fuse_mlp: true flash_attn_fuse_qkv: false flash_attn_rms_norm: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 1 gradient_checkpointing: true group_by_length: false learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: null lora_dropout: null lora_fan_in_fan_out: null lora_model_dir: null lora_r: null lora_target_linear: null lr_scheduler: cosine micro_batch_size: 1 model_type: LlamaForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: ./TinyLlama-Tinybook-epochs-1-lr-0002_Train_On_Input pad_to_sequence_len: true resume_from_checkpoint: null sample_packing: true saves_per_epoch: 1 sequence_len: 2048 special_tokens: null strict: false tf32: false tokenizer_type: LlamaTokenizer train_on_inputs: true val_set_size: 0.05 wandb_entity: utrgvmedai wandb_log_model: null wandb_name: tinyLama_Tinybook_epochs_1_lr_0002 wandb_project: TinyLlama-Train-On-Input wandb_watch: null warmup_steps: 100 weight_decay: 0.1 xformers_attention: null ```

# TinyLlama-Tinybook-epochs-1-lr-0002_Train_On_Input This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8024 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.7259 | 0.04 | 1 | 1.9138 | | 1.8155 | 0.26 | 6 | 1.9014 | | 1.8636 | 0.52 | 12 | 1.8655 | | 1.8758 | 0.78 | 18 | 1.8024 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.0