billsum_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5317
- Rouge1: 0.1432
- Rouge2: 0.0557
- Rougel: 0.12
- Rougelsum: 0.1198
- Gen Len: 19.0
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | 2.8257 | 0.1296 | 0.0369 | 0.1079 | 0.1081 | 19.0 |
No log | 2.0 | 124 | 2.6123 | 0.1368 | 0.0487 | 0.1149 | 0.1149 | 19.0 |
No log | 3.0 | 186 | 2.5482 | 0.1421 | 0.0546 | 0.1187 | 0.1184 | 19.0 |
No log | 4.0 | 248 | 2.5317 | 0.1432 | 0.0557 | 0.12 | 0.1198 | 19.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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google-t5/t5-small