t5-small-turkish-summarisation-lora
This model is a fine-tuned version of google-t5/t5-small on the mlsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.0317
- Rouge1: 19.4302
- Rouge2: 13.1054
- Rougel: 18.7905
- Rougelsum: 18.8397
- Gen Len: 20.0
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.557 | 1.0 | 624 | 2.1852 | 18.4642 | 11.9852 | 17.839 | 18.0458 | 20.0 |
| 2.364 | 2.0 | 1248 | 2.1269 | 19.6197 | 13.135 | 18.9274 | 19.0553 | 19.9913 |
| 2.3235 | 3.0 | 1872 | 2.0928 | 19.5088 | 13.2191 | 18.8665 | 18.9558 | 20.0 |
| 2.3002 | 4.0 | 2496 | 2.0669 | 19.2649 | 12.9427 | 18.6374 | 18.6937 | 20.0 |
| 2.2803 | 5.0 | 3120 | 2.0542 | 19.427 | 13.1022 | 18.7882 | 18.8376 | 20.0 |
| 2.2731 | 6.0 | 3744 | 2.0412 | 19.4496 | 13.1266 | 18.8102 | 18.8668 | 20.0 |
| 2.2655 | 7.0 | 4368 | 2.0338 | 19.4302 | 13.1054 | 18.7905 | 18.8397 | 20.0 |
| 2.2611 | 8.0 | 4992 | 2.0323 | 19.4302 | 13.1054 | 18.7905 | 18.8397 | 20.0 |
| 2.2584 | 9.0 | 5616 | 2.0321 | 19.4302 | 13.1054 | 18.7905 | 18.8397 | 20.0 |
| 2.2533 | 10.0 | 6240 | 2.0317 | 19.4302 | 13.1054 | 18.7905 | 18.8397 | 20.0 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.2.2
- Datasets 3.2.0
- Tokenizers 0.21.0