billsum_model
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5203
- Rouge1: 0.1478
- Rouge2: 0.0536
- Rougel: 0.1237
- Rougelsum: 0.1236
- Gen Len: 20.0
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: 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.8114 | 0.132 | 0.0395 | 0.1117 | 0.1115 | 20.0 |
| No log | 2.0 | 124 | 2.5983 | 0.1384 | 0.0478 | 0.1169 | 0.1169 | 20.0 |
| No log | 3.0 | 186 | 2.5372 | 0.1468 | 0.0545 | 0.1236 | 0.1235 | 20.0 |
| No log | 4.0 | 248 | 2.5203 | 0.1478 | 0.0536 | 0.1237 | 0.1236 | 20.0 |
Framework versions
- Transformers 5.0.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Base model
google-t5/t5-small