--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - eur-lex-sum metrics: - rouge model-index: - name: T5_small_eurlexsum results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: eur-lex-sum type: eur-lex-sum config: french split: test args: french metrics: - name: Rouge1 type: rouge value: 0.2 --- # T5_small_eurlexsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eur-lex-sum dataset. It achieves the following results on the evaluation set: - Loss: 1.1159 - Rouge1: 0.2 - Rouge2: 0.1394 - Rougel: 0.1833 - Rougelsum: 0.1829 - 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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 71 | 1.4740 | 0.1718 | 0.0935 | 0.1476 | 0.1476 | 19.0 | | No log | 2.0 | 142 | 1.2138 | 0.1915 | 0.1207 | 0.1719 | 0.1719 | 19.0 | | No log | 3.0 | 213 | 1.1368 | 0.1953 | 0.1306 | 0.1759 | 0.1759 | 19.0 | | No log | 4.0 | 284 | 1.1159 | 0.2 | 0.1394 | 0.1833 | 0.1829 | 19.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.0 - Tokenizers 0.13.3