metadata
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned-billsum
results: []
t5-base-finetuned-billsum
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: 1.1725
- Rouge1: 54.1481
- Rouge2: 33.3953
- Rougel: 42.8337
- Rougelsum: 47.5287
- Gen Len: 116.8581
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
2.5944 | 0.4219 | 500 | 1.2582 | 50.6899 | 31.6418 | 40.2325 | 44.2687 | 111.7541 |
1.3588 | 0.8439 | 1000 | 1.1591 | 55.865 | 35.992 | 44.7636 | 49.2805 | 114.3552 |
1.275 | 1.2658 | 1500 | 1.1214 | 56.3449 | 37.0781 | 45.604 | 49.9711 | 110.7724 |
1.3266 | 1.6878 | 2000 | 1.1791 | 54.4797 | 33.8689 | 43.1813 | 47.8507 | 114.8278 |
1.3591 | 2.1097 | 2500 | 1.1725 | 54.243 | 33.5179 | 42.9187 | 47.6231 | 116.4601 |
1.3484 | 2.5316 | 3000 | 1.1724 | 54.1433 | 33.3914 | 42.8348 | 47.5267 | 116.7736 |
1.3467 | 2.9536 | 3500 | 1.1724 | 54.1359 | 33.3794 | 42.8167 | 47.5153 | 116.7819 |
1.3483 | 3.3755 | 4000 | 1.1724 | 54.1446 | 33.3947 | 42.8274 | 47.5313 | 116.8529 |
1.342 | 3.7975 | 4500 | 1.1724 | 54.1341 | 33.3888 | 42.8239 | 47.5291 | 116.7957 |
1.3475 | 4.2194 | 5000 | 1.1725 | 54.1411 | 33.3931 | 42.8224 | 47.5218 | 116.8229 |
1.3542 | 4.6414 | 5500 | 1.1725 | 54.1481 | 33.3953 | 42.8337 | 47.5287 | 116.8581 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1