new_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: 2.5708
- Rouge1: 0.1481
- Rouge2: 0.0573
- Rougel: 0.1218
- Rougelsum: 0.1218
- 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 | 2.8582 | 0.1322 | 0.0407 | 0.1092 | 0.1093 | 20.0 |
No log | 2.0 | 124 | 2.6452 | 0.1483 | 0.0578 | 0.1229 | 0.1227 | 20.0 |
No log | 3.0 | 186 | 2.5852 | 0.1503 | 0.06 | 0.1244 | 0.1243 | 20.0 |
No log | 4.0 | 248 | 2.5708 | 0.1481 | 0.0573 | 0.1218 | 0.1218 | 20.0 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Base model
google-t5/t5-small