--- license: apache-2.0 base_model: buianh0803/text-sum tags: - generated_from_trainer datasets: - cnn_dailymail metrics: - rouge model-index: - name: text-sum-2 results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: cnn_dailymail type: cnn_dailymail config: 3.0.0 split: test args: 3.0.0 metrics: - name: Rouge1 type: rouge value: 0.2485 --- # text-sum-2 This model is a fine-tuned version of [buianh0803/text-sum](https://huggingface.co/buianh0803/text-sum) on the cnn_dailymail dataset. It achieves the following results on the evaluation set: - Loss: 1.6574 - Rouge1: 0.2485 - Rouge2: 0.1188 - Rougel: 0.2056 - Rougelsum: 0.2056 - Gen Len: 18.9991 ## 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 | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | 1.7956 | 1.0 | 17945 | 1.6629 | 0.2481 | 0.1182 | 0.2053 | 0.2054 | 18.999 | | 1.7865 | 2.0 | 35890 | 1.6576 | 0.2479 | 0.1181 | 0.2049 | 0.205 | 18.9987 | | 1.7697 | 3.0 | 53835 | 1.6574 | 0.2485 | 0.1188 | 0.2056 | 0.2056 | 18.9991 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1