metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
results: []
my_awesome_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: 2.5680
- Rouge1: 0.1434
- Rouge2: 0.0458
- Rougel: 0.118
- Rougelsum: 0.1182
- 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 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 | 62 | 2.8554 | 0.1344 | 0.04 | 0.113 | 0.1131 | 20.0 |
| No log | 2.0 | 124 | 2.6474 | 0.1374 | 0.0431 | 0.1142 | 0.1142 | 20.0 |
| No log | 3.0 | 186 | 2.5835 | 0.1413 | 0.0449 | 0.1159 | 0.1161 | 20.0 |
| No log | 4.0 | 248 | 2.5680 | 0.1434 | 0.0458 | 0.118 | 0.1182 | 20.0 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0