t5-small-legal-summarizer
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9930
- Rouge1: 22.9243
- Rouge2: 7.1417
- Rougel: 18.8502
- Rougelsum: 19.6924
- Gen Len: 17.5222
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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 89 | 3.0995 | 23.1688 | 7.6038 | 19.0864 | 20.241 | 18.1778 |
| No log | 2.0 | 178 | 3.0162 | 23.35 | 7.1787 | 19.2791 | 20.0032 | 17.6222 |
| No log | 3.0 | 267 | 2.9930 | 22.9243 | 7.1417 | 18.8502 | 19.6924 | 17.5222 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1