--- license: gemma library_name: peft tags: - alignment-handbook - trl - sft - generated_from_trainer base_model: google/gemma-7b datasets: - chansung/merged_ds_coding model-index: - name: coding_llamaduo_result1 results: [] --- # coding_llamaduo_result1 This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the chansung/merged_ds_coding dataset. It achieves the following results on the evaluation set: - Loss: 1.1871 ## 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: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - total_eval_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.5404 | 0.99 | 36 | 1.5048 | | 0.9147 | 2.0 | 73 | 1.2327 | | 0.7658 | 2.99 | 109 | 1.1766 | | 0.6657 | 4.0 | 146 | 1.1664 | | 0.5601 | 4.93 | 180 | 1.1871 | ### Framework versions - PEFT 0.7.1 - Transformers 4.39.3 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2