--- base_model: microsoft/phi-2 datasets: - generator library_name: peft license: mit tags: - trl - sft - generated_from_trainer model-index: - name: ERC_SUMMARY_phi2_peft results: [] --- [Visualize in Weights & Biases](https://wandb.ai/gladys-vimalan-anna-university/ERC_PEFT_phi2/runs/a2dnk0qv) # ERC_SUMMARY_phi2_peft This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the ArunaMak/ERC_summary dataset. It achieves the following results on the evaluation set: - Loss: 1.4798 ## 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: 1e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 6 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.5888 | 1.0 | 40 | 1.5819 | | 1.5677 | 2.0 | 80 | 1.5202 | | 1.5819 | 3.0 | 120 | 1.4962 | | 1.4227 | 4.0 | 160 | 1.4842 | | 1.4786 | 5.0 | 200 | 1.4798 | | 1.5015 | 6.0 | 240 | 1.4798 | ### Framework versions - PEFT 0.12.0 - Transformers 4.43.0.dev0 - Pytorch 2.3.1+cu118 - Datasets 2.20.0 - Tokenizers 0.19.1