t5-small-finetuned-Lucence
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1174
- Rouge2 Precision: 0.7295
- Rouge2 Recall: 0.6986
- Rouge2 Fmeasure: 0.7058
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: 5e-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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.1645 | 1.0 | 2914 | 0.1430 | 0.6893 | 0.6558 | 0.6632 |
| 0.1399 | 2.0 | 5828 | 0.1276 | 0.7171 | 0.6826 | 0.6912 |
| 0.1288 | 3.0 | 8742 | 0.1215 | 0.7238 | 0.6924 | 0.6997 |
| 0.122 | 4.0 | 11656 | 0.1182 | 0.7276 | 0.6963 | 0.7037 |
| 0.1196 | 5.0 | 14570 | 0.1174 | 0.7295 | 0.6986 | 0.7058 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3