mt5-small-finetuned-news-summary-model-2
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5813
- Rouge1: 29.4322
- Rouge2: 11.4361
- Rougel: 26.3875
- Rougelsum: 26.297
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: 4e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 9.2632 | 0.9972 | 351 | 3.7059 | 17.3365 | 5.2307 | 15.438 | 15.3776 |
| 4.6719 | 1.9943 | 702 | 3.0896 | 19.5787 | 6.8278 | 18.0637 | 18.0255 |
| 4.1356 | 2.9915 | 1053 | 2.8713 | 22.5668 | 8.2899 | 20.551 | 20.5232 |
| 3.7852 | 3.9886 | 1404 | 2.7729 | 25.7974 | 9.9158 | 23.2398 | 23.2198 |
| 3.6194 | 4.9858 | 1755 | 2.7038 | 26.2572 | 10.0034 | 24.0326 | 23.9956 |
| 3.4864 | 5.9830 | 2106 | 2.6714 | 26.8149 | 9.9056 | 24.2704 | 24.1399 |
| 3.3965 | 6.9801 | 2457 | 2.6361 | 27.5399 | 10.3609 | 24.8286 | 24.7628 |
| 3.3422 | 7.9773 | 2808 | 2.6194 | 28.0298 | 10.6938 | 25.1678 | 25.0924 |
| 3.2879 | 8.9744 | 3159 | 2.5976 | 28.2324 | 10.6412 | 25.2803 | 25.1804 |
| 3.2391 | 9.9716 | 3510 | 2.5894 | 29.0155 | 11.174 | 25.9995 | 25.8843 |
| 3.2128 | 10.9688 | 3861 | 2.5854 | 29.3283 | 11.477 | 26.2235 | 26.1278 |
| 3.2214 | 11.9659 | 4212 | 2.5813 | 29.4322 | 11.4361 | 26.3875 | 26.297 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
google/mt5-small