hg_bill_summarize_train
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: 2.4521
- Rouge1: 0.1479
- Rouge2: 0.0544
- Rougel: 0.1234
- Rougelsum: 0.1234
- 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: 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 | 2.5782 | 0.1304 | 0.0429 | 0.1087 | 0.1088 | 19.0 |
| No log | 2.0 | 124 | 2.4955 | 0.1378 | 0.0463 | 0.1138 | 0.1139 | 19.0 |
| No log | 3.0 | 186 | 2.4624 | 0.1469 | 0.0536 | 0.1217 | 0.1219 | 19.0 |
| No log | 4.0 | 248 | 2.4521 | 0.1479 | 0.0544 | 0.1234 | 0.1234 | 19.0 |
Framework versions
- Transformers 5.20.2
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.3