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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: bart-large-cnn-finetuned-quran
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-large-cnn-finetuned-quran
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0519
## 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: 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7497 | 1.0 | 99 | 0.2608 |
| 0.1367 | 2.0 | 198 | 0.0607 |
| 0.0658 | 3.0 | 297 | 0.0529 |
| 0.0563 | 4.0 | 396 | 0.0521 |
| 0.0575 | 5.0 | 495 | 0.0522 |
| 0.0489 | 6.0 | 594 | 0.0518 |
| 0.0503 | 7.0 | 693 | 0.0511 |
| 0.0494 | 8.0 | 792 | 0.0532 |
| 0.0496 | 9.0 | 891 | 0.0512 |
| 0.0494 | 10.0 | 990 | 0.0515 |
| 0.051 | 11.0 | 1089 | 0.0517 |
| 0.0508 | 12.0 | 1188 | 0.0509 |
| 0.0543 | 13.0 | 1287 | 0.0516 |
| 0.0471 | 14.0 | 1386 | 0.0520 |
| 0.0483 | 15.0 | 1485 | 0.0519 |
| 0.0469 | 16.0 | 1584 | 0.0516 |
| 0.0478 | 17.0 | 1683 | 0.0514 |
| 0.0477 | 18.0 | 1782 | 0.0513 |
| 0.0479 | 19.0 | 1881 | 0.0511 |
| 0.0473 | 20.0 | 1980 | 0.0512 |
| 0.046 | 21.0 | 2079 | 0.0522 |
| 0.0481 | 22.0 | 2178 | 0.0514 |
| 0.0477 | 23.0 | 2277 | 0.0513 |
| 0.0476 | 24.0 | 2376 | 0.0514 |
| 0.047 | 25.0 | 2475 | 0.0517 |
| 0.0477 | 26.0 | 2574 | 0.0515 |
| 0.0461 | 27.0 | 2673 | 0.0515 |
| 0.0458 | 28.0 | 2772 | 0.0516 |
| 0.0463 | 29.0 | 2871 | 0.0518 |
| 0.0471 | 30.0 | 2970 | 0.0514 |
| 0.0452 | 31.0 | 3069 | 0.0518 |
| 0.0441 | 32.0 | 3168 | 0.0515 |
| 0.0477 | 33.0 | 3267 | 0.0519 |
| 0.0467 | 34.0 | 3366 | 0.0518 |
| 0.0464 | 35.0 | 3465 | 0.0515 |
| 0.045 | 36.0 | 3564 | 0.0517 |
| 0.0445 | 37.0 | 3663 | 0.0517 |
| 0.0449 | 38.0 | 3762 | 0.0515 |
| 0.0449 | 39.0 | 3861 | 0.0518 |
| 0.0454 | 40.0 | 3960 | 0.0518 |
| 0.0452 | 41.0 | 4059 | 0.0518 |
| 0.0448 | 42.0 | 4158 | 0.0518 |
| 0.0446 | 43.0 | 4257 | 0.0519 |
| 0.0448 | 44.0 | 4356 | 0.0519 |
| 0.0443 | 45.0 | 4455 | 0.0519 |
| 0.0452 | 46.0 | 4554 | 0.0519 |
| 0.0429 | 47.0 | 4653 | 0.0519 |
| 0.0455 | 48.0 | 4752 | 0.0519 |
| 0.0452 | 49.0 | 4851 | 0.0519 |
| 0.0441 | 50.0 | 4950 | 0.0519 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3
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