flan-t5-base-turkish-summarisation-qlora
This model is a fine-tuned version of google/flan-t5-base on the mlsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.3322
- Rouge1: 17.1573
- Rouge2: 11.0617
- Rougel: 16.4608
- Rougelsum: 16.5524
- 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: 4
- eval_batch_size: 4
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.6967 | 0.0802 | 1000 | 1.3809 | 17.1243 | 10.8379 | 16.3406 | 16.4851 | 19.9931 |
| 1.5702 | 0.1605 | 2000 | 1.3652 | 17.1131 | 10.9041 | 16.3464 | 16.4593 | 20.0 |
| 1.5445 | 0.2407 | 3000 | 1.3527 | 17.1524 | 11.0021 | 16.417 | 16.5102 | 20.0 |
| 1.5434 | 0.3209 | 4000 | 1.3503 | 17.102 | 10.9546 | 16.3797 | 16.4841 | 20.0 |
| 1.5155 | 0.4012 | 5000 | 1.3451 | 17.1088 | 10.9964 | 16.3958 | 16.4918 | 20.0 |
| 1.5344 | 0.4814 | 6000 | 1.3392 | 17.1348 | 10.9911 | 16.4023 | 16.4937 | 20.0 |
| 1.5197 | 0.5616 | 7000 | 1.3461 | 17.1305 | 11.0374 | 16.4125 | 16.5098 | 20.0 |
| 1.4971 | 0.6418 | 8000 | 1.3360 | 17.1411 | 11.0398 | 16.4332 | 16.5279 | 20.0 |
| 1.5239 | 0.7221 | 9000 | 1.3350 | 17.0932 | 10.9845 | 16.3934 | 16.498 | 20.0 |
| 1.5081 | 0.8023 | 10000 | 1.3347 | 17.1313 | 11.0259 | 16.4294 | 16.5297 | 20.0 |
| 1.4829 | 0.8825 | 11000 | 1.3312 | 17.1703 | 11.0584 | 16.4678 | 16.5651 | 20.0 |
| 1.5018 | 0.9628 | 12000 | 1.3322 | 17.1573 | 11.0617 | 16.4608 | 16.5524 | 20.0 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.2.2
- Datasets 3.2.0
- Tokenizers 0.21.0