metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_summarization_model
results: []
my_summarization_model
This model is a fine-tuned version of google-t5/t5-small on an billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.2280
- Rouge1: 0.4067
- Rouge2: 0.1832
- Rougel: 0.2719
- Rougelsum: 0.2717
- Gen Len: 126.8427
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 124 | 2.5595 | 0.3549 | 0.1384 | 0.2234 | 0.2233 | 123.0242 |
| No log | 2.0 | 248 | 2.4759 | 0.3779 | 0.1517 | 0.2462 | 0.2461 | 124.0323 |
| No log | 3.0 | 372 | 2.4305 | 0.3921 | 0.1647 | 0.2583 | 0.2582 | 126.379 |
| No log | 4.0 | 496 | 2.3922 | 0.393 | 0.1666 | 0.2609 | 0.261 | 126.1089 |
| 2.651 | 5.0 | 620 | 2.3726 | 0.3956 | 0.1689 | 0.2637 | 0.2641 | 126.3831 |
| 2.651 | 6.0 | 744 | 2.3473 | 0.3985 | 0.1736 | 0.2666 | 0.2669 | 126.4153 |
| 2.651 | 7.0 | 868 | 2.3269 | 0.3991 | 0.1717 | 0.2651 | 0.2651 | 126.4315 |
| 2.651 | 8.0 | 992 | 2.3154 | 0.3964 | 0.1695 | 0.2648 | 0.2647 | 126.5161 |
| 2.4496 | 9.0 | 1116 | 2.3047 | 0.4022 | 0.1755 | 0.2695 | 0.2694 | 126.5726 |
| 2.4496 | 10.0 | 1240 | 2.2988 | 0.4021 | 0.1758 | 0.27 | 0.2699 | 126.5161 |
| 2.4496 | 11.0 | 1364 | 2.2797 | 0.4033 | 0.1779 | 0.2718 | 0.2716 | 126.5726 |
| 2.4496 | 12.0 | 1488 | 2.2765 | 0.4072 | 0.1804 | 0.2719 | 0.2718 | 126.4758 |
| 2.3631 | 13.0 | 1612 | 2.2661 | 0.4074 | 0.1797 | 0.2722 | 0.2723 | 126.6452 |
| 2.3631 | 14.0 | 1736 | 2.2585 | 0.4042 | 0.1769 | 0.27 | 0.2698 | 126.6089 |
| 2.3631 | 15.0 | 1860 | 2.2539 | 0.4066 | 0.1797 | 0.2721 | 0.2722 | 126.6613 |
| 2.3631 | 16.0 | 1984 | 2.2497 | 0.403 | 0.176 | 0.2696 | 0.2697 | 126.6371 |
| 2.3203 | 17.0 | 2108 | 2.2438 | 0.4038 | 0.1783 | 0.2706 | 0.2707 | 126.7339 |
| 2.3203 | 18.0 | 2232 | 2.2375 | 0.4034 | 0.1787 | 0.2691 | 0.2693 | 126.7903 |
| 2.3203 | 19.0 | 2356 | 2.2354 | 0.4016 | 0.1779 | 0.2676 | 0.2677 | 126.8427 |
| 2.3203 | 20.0 | 2480 | 2.2334 | 0.4041 | 0.1787 | 0.2697 | 0.2697 | 126.8952 |
| 2.285 | 21.0 | 2604 | 2.2315 | 0.4026 | 0.1797 | 0.2694 | 0.2693 | 126.7903 |
| 2.285 | 22.0 | 2728 | 2.2302 | 0.4044 | 0.1804 | 0.27 | 0.27 | 126.7903 |
| 2.285 | 23.0 | 2852 | 2.2284 | 0.4055 | 0.1827 | 0.2716 | 0.2714 | 126.7379 |
| 2.285 | 24.0 | 2976 | 2.2283 | 0.4061 | 0.1825 | 0.2716 | 0.2715 | 126.7903 |
| 2.2698 | 25.0 | 3100 | 2.2280 | 0.4067 | 0.1832 | 0.2719 | 0.2717 | 126.8427 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1