metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5_base_fine_tuned
results: []
T5_base_fine_tuned
This model is a fine-tuned version of google-t5/t5-base on the BillSum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1618
- Rouge1: 0.1578
- Rouge2: 0.0635
- Rougel: 0.1288
- Rougelsum: 0.1288
- 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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.487 | 1.0 | 1000 | 2.1837 | 0.1507 | 0.0586 | 0.1233 | 0.1233 | 19.0 |
| 1.4014 | 2.0 | 2000 | 2.1688 | 0.1571 | 0.0639 | 0.1282 | 0.1282 | 19.0 |
| 1.3501 | 3.0 | 3000 | 2.1673 | 0.1564 | 0.063 | 0.1283 | 0.1283 | 19.0 |
| 1.3332 | 4.0 | 4000 | 2.1618 | 0.1578 | 0.0635 | 0.1288 | 0.1288 | 19.0 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3