--- base_model: google/gemma-2-2b-it datasets: - GaetanMichelet/chat-60_ft_task-2_auto - GaetanMichelet/chat-120_ft_task-2_auto library_name: peft license: gemma tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: Gemma-2-2B_task-2_120-samples_config-2_full_auto results: [] --- # Gemma-2-2B_task-2_120-samples_config-2_full_auto This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on the GaetanMichelet/chat-60_ft_task-2_auto and the GaetanMichelet/chat-120_ft_task-2_auto datasets. It achieves the following results on the evaluation set: - Loss: 0.8633 ## 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: 0.0001 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 16 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:----:|:---------------:| | 1.3338 | 0.9091 | 5 | 1.3082 | | 1.3005 | 2.0 | 11 | 1.2187 | | 1.1249 | 2.9091 | 16 | 1.1211 | | 1.0441 | 4.0 | 22 | 1.0411 | | 0.9601 | 4.9091 | 27 | 0.9654 | | 0.8731 | 6.0 | 33 | 0.9165 | | 0.8553 | 6.9091 | 38 | 0.8962 | | 0.8229 | 8.0 | 44 | 0.8815 | | 0.7958 | 8.9091 | 49 | 0.8724 | | 0.7945 | 10.0 | 55 | 0.8658 | | 0.7557 | 10.9091 | 60 | 0.8634 | | 0.7322 | 12.0 | 66 | 0.8633 | | 0.7081 | 12.9091 | 71 | 0.8664 | | 0.6938 | 14.0 | 77 | 0.8733 | | 0.6136 | 14.9091 | 82 | 0.8832 | | 0.6249 | 16.0 | 88 | 0.8980 | | 0.573 | 16.9091 | 93 | 0.9280 | | 0.5309 | 18.0 | 99 | 0.9385 | | 0.5198 | 18.9091 | 104 | 0.9874 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1