T5-small_finetuned_billsum_subset_model_bs16_lr2e-05
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.0305
- Rouge1: 0.1931
- Rouge2: 0.0965
- Rougel: 0.1667
- Rougelsum: 0.1662
- Gen Len: 19.0
- Bleu: 0.0008
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 | Bleu |
|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.0395 | 0.1922 | 0.0973 | 0.1672 | 0.1668 | 19.0 | 0.0008 |
| No log | 2.0 | 124 | 2.0364 | 0.1932 | 0.0973 | 0.1685 | 0.1681 | 19.0 | 0.0008 |
| No log | 3.0 | 186 | 2.0323 | 0.1921 | 0.0968 | 0.1671 | 0.1666 | 19.0 | 0.0008 |
| No log | 4.0 | 248 | 2.0305 | 0.1931 | 0.0965 | 0.1667 | 0.1662 | 19.0 | 0.0008 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3