billsum-model-z
This model is a fine-tuned version of google-t5/t5-base on an FiscalNote/billsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.9649
- Rouge1: 0.473
- Rouge2: 0.2725
- Rougel: 0.3613
- Rougelsum: 0.3612
- Gen Len: 129.5922
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
2.2403 | 1.0 | 4738 | 2.0142 | 0.470 | 0.2680 | 0.3586 | 0.3585 | 130.1138 |
2.1743 | 2.0 | 9476 | 1.9649 | 0.473 | 0.2725 | 0.3613 | 0.3612 | 129.5922 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-t5/t5-base