text-summarization
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5397
- Rouge1: 0.1306
- Rouge2: 0.0442
- Rougel: 0.1096
- Rougelsum: 0.1093
- 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: 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.8278 | 0.1276 | 0.0368 | 0.1083 | 0.1078 | 19.0 |
| No log | 2.0 | 124 | 2.6203 | 0.1333 | 0.0459 | 0.1127 | 0.1125 | 19.0 |
| No log | 3.0 | 186 | 2.5566 | 0.1292 | 0.0434 | 0.1075 | 0.1074 | 19.0 |
| No log | 4.0 | 248 | 2.5397 | 0.1306 | 0.0442 | 0.1096 | 0.1093 | 19.0 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2