--- library_name: transformers license: apache-2.0 base_model: google-t5/t5-small tags: - generated_from_trainer metrics: - rouge model-index: - name: summarization_model results: [] --- # summarization_model 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: 2.5063 - Rouge1: 0.1509 - Rouge2: 0.056 - Rougel: 0.124 - Rougelsum: 0.1243 - Gen Len: 20.0 ## 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 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: 4 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 62 | 2.7890 | 0.1382 | 0.0435 | 0.1136 | 0.1139 | 20.0 | | No log | 2.0 | 124 | 2.5839 | 0.1486 | 0.0533 | 0.1223 | 0.1221 | 20.0 | | No log | 3.0 | 186 | 2.5227 | 0.1512 | 0.0565 | 0.1241 | 0.1245 | 20.0 | | No log | 4.0 | 248 | 2.5063 | 0.1509 | 0.056 | 0.124 | 0.1243 | 20.0 | ### Framework versions - Transformers 4.53.2 - Pytorch 2.9.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4