T5-Small-Sinhala-Sumarization-test3
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1131
- Rouge1: 0.0507
- Rouge2: 0.0123
- Rougel: 0.0494
- Rougelsum: 0.0492
- Gen Len: 19.0
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 5.9823 | 1.0 | 600 | 5.3762 | 0.0259 | 0.0043 | 0.025 | 0.0248 | 19.0 |
| 5.5041 | 2.0 | 1200 | 5.2242 | 0.0356 | 0.0089 | 0.0352 | 0.0353 | 19.0 |
| 5.4129 | 3.0 | 1800 | 5.1601 | 0.0469 | 0.0104 | 0.0457 | 0.0457 | 19.0 |
| 5.3062 | 4.0 | 2400 | 5.1225 | 0.049 | 0.0119 | 0.0476 | 0.0475 | 19.0 |
| 5.2787 | 5.0 | 3000 | 5.1131 | 0.0507 | 0.0123 | 0.0494 | 0.0492 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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