--- 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: 0.2288 --- # 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: 0.9360 - Rouge1: 0.2288 - Rouge2: 0.1816 - Rougel: 0.2157 - Rougelsum: 0.2158 - 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: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 71 | 1.4482 | 0.1743 | 0.0982 | 0.1509 | 0.1511 | 19.0 | | No log | 2.0 | 142 | 1.1661 | 0.193 | 0.1257 | 0.1731 | 0.1734 | 19.0 | | No log | 3.0 | 213 | 1.0651 | 0.2072 | 0.1483 | 0.1892 | 0.1896 | 19.0 | | No log | 4.0 | 284 | 1.0053 | 0.2167 | 0.1638 | 0.2017 | 0.2019 | 19.0 | | No log | 5.0 | 355 | 0.9706 | 0.222 | 0.1731 | 0.2082 | 0.2079 | 19.0 | | No log | 6.0 | 426 | 0.9510 | 0.2253 | 0.1771 | 0.2114 | 0.2114 | 19.0 | | No log | 7.0 | 497 | 0.9393 | 0.2263 | 0.1785 | 0.2134 | 0.2133 | 19.0 | | 1.4549 | 8.0 | 568 | 0.9360 | 0.2288 | 0.1816 | 0.2157 | 0.2158 | 19.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.13.1 - Tokenizers 0.13.3