--- 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-gpt4o-256k results: [] --- # gemma7b-summarize-gpt4o-256k 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: 2.4681 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 1.0805 | 1.0 | 439 | 2.5210 | | 0.9397 | 2.0 | 878 | 2.4361 | | 0.8628 | 3.0 | 1317 | 2.4056 | | 0.8131 | 4.0 | 1756 | 2.4177 | | 0.7788 | 5.0 | 2195 | 2.4166 | | 0.771 | 6.0 | 2634 | 2.4329 | | 0.7459 | 7.0 | 3073 | 2.4458 | | 0.745 | 8.0 | 3512 | 2.4609 | | 0.7433 | 9.0 | 3951 | 2.4640 | | 0.7376 | 10.0 | 4390 | 2.4681 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.1.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1