--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - cnn_dailymail metrics: - rouge model-index: - name: cnn_news_summary_model_trained_on_reduced_data results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: cnn_dailymail type: cnn_dailymail config: 3.0.0 split: train[:3%] args: 3.0.0 metrics: - name: Rouge1 type: rouge value: 0.2184 --- # cnn_news_summary_model_trained_on_reduced_data This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset. It achieves the following results on the evaluation set: - Loss: 1.5909 - Rouge1: 0.2184 - Rouge2: 0.0951 - Rougel: 0.1841 - Rougelsum: 0.1843 - Generated Length: 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:| | No log | 1.0 | 431 | 1.6006 | 0.2181 | 0.0944 | 0.1837 | 0.1838 | 19.0 | | 1.8083 | 2.0 | 862 | 1.5923 | 0.2187 | 0.0952 | 0.1842 | 0.1845 | 19.0 | | 1.8004 | 3.0 | 1293 | 1.5909 | 0.2184 | 0.0951 | 0.1841 | 0.1843 | 19.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.3 - Tokenizers 0.13.3