metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: billsum-model
results: []
billsum-model
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2894
- Rouge1: 0.4161
- Rouge2: 0.1838
- Rougel: 0.2786
- Rougelsum: 0.2791
- Gen Len: 149.0
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: 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 248 | 2.4737 | 0.3984 | 0.1645 | 0.261 | 0.2607 | 144.9718 |
| No log | 2.0 | 496 | 2.3435 | 0.4126 | 0.1783 | 0.2762 | 0.2764 | 148.754 |
| 3.4184 | 3.0 | 744 | 2.3004 | 0.4162 | 0.1814 | 0.2765 | 0.2767 | 149.0 |
| 3.4184 | 4.0 | 992 | 2.2894 | 0.4161 | 0.1838 | 0.2786 | 0.2791 | 149.0 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3