--- library_name: transformers license: apache-2.0 base_model: google/long-t5-tglobal-base tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_qwen2.5_72b results: [] --- # jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_qwen2.5_72b This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5751 - 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: 2 - eval_batch_size: 2 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.6164 | 1.0 | 92 | 0.6295 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.441 | 2.0 | 184 | 1.0194 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.5682 | 3.0 | 276 | 1.5109 | 0.7 | 0.8235 | 0.7 | 1.0 | | 1.0803 | 4.0 | 368 | 1.6351 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.9585 | 5.0 | 460 | 1.7171 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.2445 | 6.0 | 552 | 1.7306 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.7548 | 7.0 | 644 | 1.7669 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.0069 | 8.0 | 736 | 1.7511 | 0.7 | 0.8235 | 0.7 | 1.0 | | 0.499 | 9.0 | 828 | 1.7201 | 0.7 | 0.8235 | 0.7 | 1.0 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.3.0+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0