--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer metrics: - rouge model-index: - name: ted_talks_summarization results: [] --- # ted_talks_summarization This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0524 - Rouge1: 0.2688 - Rouge2: 0.0754 - Rougel: 0.1731 - Rougelsum: 0.1733 - Gen Len: 128.0 ## 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: 5e-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 - lr_scheduler_warmup_steps: 100 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | 3.4159 | 1.0 | 249 | 3.1353 | 0.2603 | 0.0652 | 0.1631 | 0.1634 | 128.0 | | 3.2981 | 2.0 | 498 | 3.0669 | 0.2673 | 0.0715 | 0.1696 | 0.1698 | 128.0 | | 3.237 | 3.0 | 747 | 3.0524 | 0.2688 | 0.0754 | 0.1731 | 0.1733 | 128.0 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0