t5-small-finetuned-summarization-app
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: 1.6614
- Rouge1: 24.5589
- Rouge2: 11.8509
- Rougel: 20.3011
- Rougelsum: 23.1768
- Gen Len: 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: 4e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8267 | 1.0 | 23927 | 1.6689 | 24.4634 | 11.7413 | 20.2154 | 23.0875 | 18.9993 |
| 1.81 | 2.0 | 47854 | 1.6614 | 24.5589 | 11.8509 | 20.3011 | 23.1768 | 19.0 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2