test-textsum-t5
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5625
- Rouge1: 0.1356
- Rouge2: 0.0464
- Rougel: 0.1141
- Rougelsum: 0.1139
- 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 | 2.8588 | 0.1248 | 0.0371 | 0.1056 | 0.1056 | 19.0 |
| No log | 2.0 | 124 | 2.6426 | 0.1301 | 0.0419 | 0.1086 | 0.1084 | 19.0 |
| No log | 3.0 | 186 | 2.5798 | 0.1347 | 0.0466 | 0.1133 | 0.1131 | 19.0 |
| No log | 4.0 | 248 | 2.5625 | 0.1356 | 0.0464 | 0.1141 | 0.1139 | 19.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3