--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: google-bert/bert-base-uncased metrics: - accuracy model-index: - name: peft_ft_fl_mod_ind results: [] --- # peft_ft_fl_mod_ind This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 11.2143 - Accuracy: -5278.2032 ## 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: 0.005 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:-----------:| | No log | 1.0 | 1 | 11.2884 | 13619.4675 | | No log | 2.0 | 2 | 12.4142 | -34586.9665 | | No log | 3.0 | 3 | 12.0917 | -36170.8404 | | No log | 4.0 | 4 | 11.3609 | -34348.1929 | | No log | 5.0 | 5 | 11.2143 | -5278.2032 | ### Framework versions - PEFT 0.11.1 - Transformers 4.41.1 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1