--- 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-gemini1_5flash-8k results: [] --- # gemma7b-summarize-gemini1_5flash-8k 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: 2.8396 ## 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 | |:-------------:|:------:|:----:|:---------------:| | 31.311 | 0.9630 | 13 | 11.0230 | | 19.0651 | 2.0 | 27 | 7.4342 | | 11.34 | 2.9630 | 40 | 6.8118 | | 3.0136 | 4.0 | 54 | 3.6308 | | 1.7786 | 4.9630 | 67 | 3.0973 | | 1.4865 | 6.0 | 81 | 2.9241 | | 1.4036 | 6.9630 | 94 | 2.8645 | | 1.3424 | 8.0 | 108 | 2.8510 | | 1.3298 | 8.9630 | 121 | 2.8410 | | 1.3245 | 9.6296 | 130 | 2.8396 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.1.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1