--- library_name: transformers license: apache-2.0 base_model: google-t5/t5-small tags: - summarization - generated_from_trainer metrics: - rouge model-index: - name: news-summarizer-t5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # news-summarizer-t5 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: 0.6177 - Model Preparation Time: 0.0049 - Rouge1: 19.8849 - Rouge2: 17.9939 - Rougel: 19.5328 - Rougelsum: 19.5918 ## 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: 0.0005 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.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: 8 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Rouge1 | Rouge2 | Rougel | Rougelsum | |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:|:-------:|:-------:|:---------:| | 0.8689 | 1.0 | 251 | 0.6581 | 0.0049 | 18.8745 | 16.2314 | 18.1991 | 18.3287 | | 0.6629 | 2.0 | 502 | 0.6385 | 0.0049 | 19.3705 | 17.1277 | 18.8685 | 18.9594 | | 0.6114 | 3.0 | 753 | 0.6294 | 0.0049 | 19.3951 | 17.2113 | 18.9315 | 18.9848 | | 0.571 | 4.0 | 1004 | 0.6197 | 0.0049 | 19.8684 | 17.8234 | 19.4646 | 19.5401 | | 0.5451 | 5.0 | 1255 | 0.6193 | 0.0049 | 19.8981 | 17.9851 | 19.5083 | 19.5177 | | 0.5194 | 6.0 | 1506 | 0.6203 | 0.0049 | 19.8675 | 17.9521 | 19.5434 | 19.6046 | | 0.4894 | 7.0 | 1757 | 0.6166 | 0.0049 | 19.8622 | 17.9616 | 19.4791 | 19.5669 | | 0.4872 | 8.0 | 2008 | 0.6177 | 0.0049 | 19.8849 | 17.9939 | 19.5328 | 19.5918 | ### Framework versions - Transformers 4.50.0 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1