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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-Kurdish-Sorani
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. -->
# whisper-small-Kurdish-Sorani
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1337
- Wer Ortho: 26.7340
- Wer: 24.1171
## 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: 1e-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
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:-------:|
| 0.3313 | 0.0248 | 250 | 0.4122 | 63.9017 | 60.4730 |
| 0.2611 | 0.0496 | 500 | 0.3482 | 55.6466 | 51.6921 |
| 0.2433 | 0.0744 | 750 | 0.3153 | 53.3507 | 49.3734 |
| 0.2208 | 0.0992 | 1000 | 0.2853 | 48.3435 | 44.5947 |
| 0.2104 | 0.1240 | 1250 | 0.2717 | 46.4543 | 42.7993 |
| 0.1828 | 0.1488 | 1500 | 0.2566 | 45.2822 | 41.3963 |
| 0.1712 | 0.1736 | 1750 | 0.2464 | 42.9045 | 39.3076 |
| 0.1695 | 0.1984 | 2000 | 0.2390 | 42.0008 | 38.2738 |
| 0.1709 | 0.2232 | 2250 | 0.2299 | 40.5875 | 36.9594 |
| 0.1601 | 0.2480 | 2500 | 0.2233 | 40.0424 | 36.5079 |
| 0.1678 | 0.2728 | 2750 | 0.2194 | 39.9124 | 36.4045 |
| 0.1534 | 0.2976 | 3000 | 0.2097 | 37.5954 | 34.0289 |
| 0.1542 | 0.3224 | 3250 | 0.2044 | 37.0712 | 33.6069 |
| 0.1493 | 0.3472 | 3500 | 0.1993 | 36.7106 | 33.3980 |
| 0.1258 | 0.3720 | 3750 | 0.1965 | 36.4086 | 32.9191 |
| 0.1212 | 0.3968 | 4000 | 0.1898 | 34.8151 | 31.4823 |
| 0.1382 | 0.4216 | 4250 | 0.1867 | 34.8297 | 31.4908 |
| 0.1368 | 0.4464 | 4500 | 0.1839 | 34.3244 | 31.1342 |
| 0.1258 | 0.4712 | 4750 | 0.1795 | 33.8673 | 30.6553 |
| 0.12 | 0.4960 | 5000 | 0.1748 | 32.6176 | 29.4126 |
| 0.1122 | 0.5208 | 5250 | 0.1699 | 32.2507 | 29.0476 |
| 0.1191 | 0.5456 | 5500 | 0.1697 | 32.4394 | 29.0603 |
| 0.1247 | 0.5704 | 5750 | 0.1629 | 31.2904 | 28.1826 |
| 0.1111 | 0.5952 | 6000 | 0.1633 | 31.8020 | 28.6341 |
| 0.1163 | 0.6200 | 6250 | 0.1587 | 30.4600 | 27.2606 |
| 0.0909 | 0.6448 | 6500 | 0.1561 | 29.8373 | 26.5433 |
| 0.0999 | 0.6696 | 6750 | 0.1534 | 29.6486 | 26.6994 |
| 0.1224 | 0.6944 | 7000 | 0.1514 | 29.0762 | 26.2353 |
| 0.0986 | 0.7192 | 7250 | 0.1496 | 28.8770 | 26.0707 |
| 0.0855 | 0.7440 | 7500 | 0.1479 | 29.1433 | 26.3492 |
| 0.0866 | 0.7688 | 7750 | 0.1456 | 28.0424 | 25.3703 |
| 0.0993 | 0.7937 | 8000 | 0.1439 | 28.1242 | 25.4040 |
| 0.1052 | 0.8185 | 8250 | 0.1414 | 27.8202 | 25.1572 |
| 0.0853 | 0.8433 | 8500 | 0.1398 | 27.6482 | 24.9757 |
| 0.0797 | 0.8681 | 8750 | 0.1383 | 27.0905 | 24.4188 |
| 0.0848 | 0.8929 | 9000 | 0.1375 | 26.9773 | 24.2141 |
| 0.1011 | 0.9177 | 9250 | 0.1356 | 26.6229 | 24.0622 |
| 0.0939 | 0.9425 | 9500 | 0.1348 | 26.7173 | 24.1803 |
| 0.0781 | 0.9673 | 9750 | 0.1341 | 26.6103 | 24.0727 |
| 0.0894 | 0.9921 | 10000 | 0.1337 | 26.7340 | 24.1171 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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