t5-small-finetuned-cnn-v2
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: 1.5474
- Rouge1: 35.154
- Rouge2: 18.683
- Rougel: 30.8481
- Rougelsum: 32.9638
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: 5.6e-05
- 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.8823 | 1.0 | 35890 | 1.5878 | 34.9676 | 18.4927 | 30.6753 | 32.7702 |
| 1.7871 | 2.0 | 71780 | 1.5709 | 34.9205 | 18.5556 | 30.6514 | 32.745 |
| 1.7507 | 3.0 | 107670 | 1.5586 | 34.9825 | 18.4964 | 30.6724 | 32.7644 |
| 1.7253 | 4.0 | 143560 | 1.5584 | 35.074 | 18.6171 | 30.8007 | 32.9132 |
| 1.705 | 5.0 | 179450 | 1.5528 | 35.023 | 18.5787 | 30.7014 | 32.8396 |
| 1.6894 | 6.0 | 215340 | 1.5518 | 35.0583 | 18.6754 | 30.791 | 32.8814 |
| 1.6776 | 7.0 | 251230 | 1.5468 | 35.2236 | 18.6812 | 30.8944 | 33.0362 |
| 1.6687 | 8.0 | 287120 | 1.5474 | 35.154 | 18.683 | 30.8481 | 32.9638 |
Framework versions
- Transformers 4.14.0
- Pytorch 1.5.0
- Datasets 2.3.2
- Tokenizers 0.10.3