--- library_name: transformers license: apache-2.0 base_model: google-t5/t5-base tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: jackmedda/google-t5-t5-base_finetuned_augmented_augmented_qwen2.5_32b results: [] --- # jackmedda/google-t5-t5-base_finetuned_augmented_augmented_qwen2.5_32b This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5638 - Accuracy: 0.7647 - F1: 0.8667 - Precision: 0.7647 - Recall: 1.0 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.4703 | 1.0 | 12 | 0.6400 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.45 | 2.0 | 24 | 0.7134 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.3933 | 3.0 | 36 | 0.7245 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.3621 | 4.0 | 48 | 0.7346 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.4332 | 5.0 | 60 | 0.6960 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.4145 | 6.0 | 72 | 0.6760 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.3738 | 7.0 | 84 | 0.6785 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.4007 | 8.0 | 96 | 0.6879 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.3578 | 9.0 | 108 | 0.7140 | 0.7 | 0.8235 | 0.7 | 1.0 | ### Framework versions - Transformers 4.48.2 - Pytorch 2.3.0+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0