metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-billsum
results: []
t5-small-billsum
This model is a fine-tuned version of google-t5/t5-small on Billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.3195
- Rouge1: 0.205
- Rouge2: 0.0994
- Rougel: 0.1708
- Rougelsum: 0.1704
- Gen Len: 20.0
Model description
More information needed
Intended uses & limitations
Research: Explore summarization performance of small models on long-text datasets like BillSum.
Applications: Legislative bill summarization (short drafts), document compression.
Not intended for production without further fine-tuning and testing.
Short outputs: Current fine-tuning capped at 20 tokens → summaries are incomplete.
Model size: T5-small struggles with very long inputs (BillSum often >512 tokens).
Performance: ROUGE scores (~0.20) are well below state-of-the-art.
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.7672 | 0.139 | 0.0457 | 0.114 | 0.1141 | 20.0 |
| No log | 2.0 | 124 | 2.5470 | 0.148 | 0.0535 | 0.121 | 0.1209 | 20.0 |
| No log | 3.0 | 186 | 2.4587 | 0.16 | 0.0645 | 0.1316 | 0.1311 | 20.0 |
| No log | 4.0 | 248 | 2.4068 | 0.1849 | 0.0833 | 0.1541 | 0.1541 | 20.0 |
| No log | 5.0 | 310 | 2.3747 | 0.1994 | 0.0945 | 0.1666 | 0.1663 | 20.0 |
| No log | 6.0 | 372 | 2.3537 | 0.2032 | 0.0976 | 0.1686 | 0.1683 | 20.0 |
| No log | 7.0 | 434 | 2.3364 | 0.203 | 0.0973 | 0.1694 | 0.169 | 20.0 |
| No log | 8.0 | 496 | 2.3259 | 0.2045 | 0.0984 | 0.1704 | 0.1701 | 20.0 |
| 2.7564 | 9.0 | 558 | 2.3217 | 0.2052 | 0.0997 | 0.1709 | 0.1704 | 20.0 |
| 2.7564 | 10.0 | 620 | 2.3195 | 0.205 | 0.0994 | 0.1708 | 0.1704 | 20.0 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4