--- 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_result2 results: [] --- # coding_llamaduo_result2 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: 1.2247 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 0.8192 | 1.0 | 122 | 1.2006 | | 0.6377 | 2.0 | 245 | 1.1304 | | 0.5334 | 3.0 | 367 | 1.1456 | | 0.4454 | 4.0 | 490 | 1.1935 | | 0.408 | 4.98 | 610 | 1.2247 | ### Framework versions - PEFT 0.7.1 - Transformers 4.39.3 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2