---
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