t5-small-billsum-ca
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 0.1984
- Rouge2: 0.0973
- Rougel: 0.1709
- Rougelsum: 0.171
- 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: 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 248 | 2.4789 | 0.15 | 0.0549 | 0.1225 | 0.1225 | 19.0 |
| No log | 2.0 | 496 | 2.3740 | 0.1932 | 0.092 | 0.1647 | 0.165 | 19.0 |
| 2.888 | 3.0 | 744 | 2.3368 | 0.1982 | 0.0967 | 0.1703 | 0.1704 | 19.0 |
| 2.888 | 4.0 | 992 | 2.3242 | 0.1984 | 0.0973 | 0.1709 | 0.171 | 19.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3