--- license: apache-2.0 tags: - generated_from_trainer datasets: - eli5 metrics: - rouge model-index: - name: t5-small-finetuned-eli5 results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: eli5 type: eli5 config: LFQA_reddit split: train_eli5 args: LFQA_reddit metrics: - name: Rouge1 type: rouge value: 9.5483 --- # t5-small-finetuned-eli5 This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eli5 dataset. It achieves the following results on the evaluation set: - Loss: 3.7596 - Rouge1: 9.5483 - Rouge2: 1.8202 - Rougel: 7.7317 - Rougelsum: 8.8491 - Gen Len: 18.9895 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | 3.9551 | 1.0 | 68159 | 3.7596 | 9.5483 | 1.8202 | 7.7317 | 8.8491 | 18.9895 | ### Framework versions - Transformers 4.22.1 - Pytorch 1.12.1+cu113 - Datasets 2.5.1 - Tokenizers 0.12.1