t5-small-finetuned-cnn-news
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 2.7209
- Rouge1: 23.5402
- Rouge2: 10.8834
- Rougel: 19.3936
- Rougelsum: 22.1513
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: 0.00056
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.2531 | 1.0 | 718 | 2.6722 | 23.3437 | 10.5433 | 19.2183 | 21.8989 |
| 2.1518 | 2.0 | 1436 | 2.7024 | 23.4068 | 10.716 | 19.0751 | 21.9328 |
| 2.0925 | 3.0 | 2154 | 2.7235 | 23.232 | 10.5236 | 19.2254 | 21.8598 |
| 2.0808 | 4.0 | 2872 | 2.7309 | 23.7401 | 10.7664 | 19.4651 | 22.2479 |
| 2.1114 | 5.0 | 3590 | 2.7209 | 23.5402 | 10.8834 | 19.3936 | 22.1513 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
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Dataset used to train hardikJ11/t5-small-finetuned-cnn-news
Evaluation results
- Rouge1 on cnn_dailymailvalidation set self-reported23.540