metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: congress_bill_summary_model
results: []
congress_bill_summary_model
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0499
- Rouge1: 0.4633
- Rouge2: 0.4498
- Rougel: 0.4635
- Rougelsum: 0.4631
- 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: 0.0002
- 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 | 14 | 0.1086 | 0.4438 | 0.4274 | 0.4427 | 0.4422 | 19.0 |
| No log | 2.0 | 28 | 0.0604 | 0.4552 | 0.4399 | 0.4551 | 0.4546 | 19.0 |
| No log | 3.0 | 42 | 0.0532 | 0.4617 | 0.4482 | 0.4623 | 0.462 | 19.0 |
| No log | 4.0 | 56 | 0.0499 | 0.4633 | 0.4498 | 0.4635 | 0.4631 | 19.0 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.0