t5_small__billsum_model
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4784
- Rouge1: 0.1405
- Rouge2: 0.0526
- Rougel: 0.1183
- Rougelsum: 0.1185
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.7739 | 0.1225 | 0.0355 | 0.1026 | 0.1028 | 19.0 |
| No log | 2.0 | 124 | 2.5588 | 0.135 | 0.0494 | 0.1147 | 0.1148 | 19.0 |
| No log | 3.0 | 186 | 2.4953 | 0.1387 | 0.0516 | 0.1173 | 0.1175 | 19.0 |
| No log | 4.0 | 248 | 2.4784 | 0.1405 | 0.0526 | 0.1183 | 0.1185 | 19.0 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3