T5-Small_Text-Summarization
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6045
- Rouge1: 0.2389
- Rouge2: 0.1905
- Rougel: 0.2306
- Rougelsum: 0.2307
- Gen Len: 18.9982
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9769 | 1.0 | 1895 | 1.7147 | 0.2325 | 0.1837 | 0.2227 | 0.2227 | 19.0 |
| 1.837 | 2.0 | 3790 | 1.6430 | 0.2369 | 0.1884 | 0.2283 | 0.2283 | 19.0 |
| 1.7849 | 3.0 | 5685 | 1.6137 | 0.2387 | 0.1901 | 0.2304 | 0.2304 | 18.9982 |
| 1.7791 | 4.0 | 7580 | 1.6045 | 0.2389 | 0.1905 | 0.2306 | 0.2307 | 18.9982 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0