--- base_model: google/gemma-2-2b-it datasets: - GaetanMichelet/chat-60_ft_task-3 library_name: peft license: gemma tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: Gemma-2-2B_task-3_60-samples_config-2_full results: [] --- # Gemma-2-2B_task-3_60-samples_config-2_full 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-3 dataset. It achieves the following results on the evaluation set: - Loss: 0.9617 ## 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 | |:-------------:|:-------:|:----:|:---------------:| | 1.3564 | 0.6957 | 2 | 1.3659 | | 1.3765 | 1.7391 | 5 | 1.3404 | | 1.3125 | 2.7826 | 8 | 1.2526 | | 1.2213 | 3.8261 | 11 | 1.1815 | | 1.1432 | 4.8696 | 14 | 1.1329 | | 1.0949 | 5.9130 | 17 | 1.0849 | | 1.0142 | 6.9565 | 20 | 1.0435 | | 0.9925 | 8.0 | 23 | 1.0153 | | 0.9508 | 8.6957 | 25 | 1.0030 | | 0.9191 | 9.7391 | 28 | 0.9871 | | 0.9172 | 10.7826 | 31 | 0.9778 | | 0.892 | 11.8261 | 34 | 0.9705 | | 0.8585 | 12.8696 | 37 | 0.9655 | | 0.8535 | 13.9130 | 40 | 0.9630 | | 0.8316 | 14.9565 | 43 | 0.9618 | | 0.8242 | 16.0 | 46 | 0.9617 | | 0.7836 | 16.6957 | 48 | 0.9622 | | 0.7962 | 17.7391 | 51 | 0.9640 | | 0.7851 | 18.7826 | 54 | 0.9657 | | 0.7553 | 19.8261 | 57 | 0.9702 | | 0.7474 | 20.8696 | 60 | 0.9767 | | 0.7352 | 21.9130 | 63 | 0.9822 | | 0.7191 | 22.9565 | 66 | 0.9871 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1