--- library_name: peft tags: - alignment-handbook - generated_from_trainer datasets: - llama-duo/synth_summarize_dataset_dedup base_model: google/gemma-7b model-index: - name: gemma7b-summarize-claude3sonnet-64k results: [] --- # gemma7b-summarize-claude3sonnet-64k This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.5547 ## 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: 4 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.1216 | 0.9967 | 150 | 2.5805 | | 0.9828 | 2.0 | 301 | 2.5169 | | 0.9157 | 2.9967 | 451 | 2.4836 | | 0.8753 | 4.0 | 602 | 2.5011 | | 0.8334 | 4.9967 | 752 | 2.4945 | | 0.796 | 6.0 | 903 | 2.5317 | | 0.7745 | 6.9967 | 1053 | 2.5436 | | 0.7582 | 8.0 | 1204 | 2.5522 | | 0.754 | 8.9967 | 1354 | 2.5504 | | 0.7572 | 9.9668 | 1500 | 2.5547 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.1.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1