--- license: apache-2.0 base_model: google-t5/t5-small tags: - summarization - generated_from_trainer metrics: - rouge model-index: - name: t5-small-finetuned-billsum results: [] --- # t5-small-finetuned-billsum This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.5533 - Rouge1: 0.1356 - Rouge2: 0.0495 - Rougel: 0.1144 - Rougelsum: 0.1144 - Gen Len: 19.0 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 62 | 2.6711 | 0.1308 | 0.0445 | 0.1107 | 0.1109 | 19.0 | | No log | 2.0 | 124 | 2.5761 | 0.1338 | 0.0483 | 0.1137 | 0.1137 | 19.0 | | No log | 3.0 | 186 | 2.5533 | 0.1356 | 0.0495 | 0.1144 | 0.1144 | 19.0 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1