t5-small-finetuned-multi-news
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8049
- Rouge1: 15.1241
- Rouge2: 4.9514
- Rougel: 11.5019
- Rougelsum: 13.3079
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.2411 | 1.0 | 1250 | 2.8772 | 14.6774 | 4.7697 | 11.335 | 13.0082 |
| 3.079 | 2.0 | 2500 | 2.8438 | 14.9558 | 4.8748 | 11.4023 | 13.2198 |
| 3.0257 | 3.0 | 3750 | 2.8240 | 15.133 | 4.9814 | 11.572 | 13.3607 |
| 2.9903 | 4.0 | 5000 | 2.8153 | 15.1339 | 4.9123 | 11.5038 | 13.3464 |
| 2.9659 | 5.0 | 6250 | 2.8085 | 15.1134 | 5.0057 | 11.5478 | 13.3483 |
| 2.9461 | 6.0 | 7500 | 2.8066 | 15.154 | 4.9641 | 11.5276 | 13.3523 |
| 2.936 | 7.0 | 8750 | 2.8049 | 15.1241 | 4.9514 | 11.5019 | 13.3079 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3