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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-10
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-10
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: 0.1166
- Wer Ortho: 14.4007
- Wer: 13.1989
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:-------:|
| 0.2207 | 0.0992 | 1000 | 0.2857 | 48.3163 | 44.5546 |
| 0.1701 | 0.1984 | 2000 | 0.2396 | 41.9819 | 38.2653 |
| 0.1551 | 0.2976 | 3000 | 0.2099 | 37.3690 | 33.9086 |
| 0.1213 | 0.3968 | 4000 | 0.1918 | 34.8926 | 31.6996 |
| 0.1205 | 0.4960 | 5000 | 0.1757 | 32.6973 | 29.4823 |
| 0.1126 | 0.5952 | 6000 | 0.1654 | 31.8523 | 28.7945 |
| 0.1229 | 0.6944 | 7000 | 0.1520 | 29.2376 | 26.4927 |
| 0.0966 | 0.7937 | 8000 | 0.1459 | 28.1116 | 25.5538 |
| 0.0805 | 0.8929 | 9000 | 0.1345 | 26.0589 | 23.7183 |
| 0.0829 | 0.9921 | 10000 | 0.1290 | 25.4676 | 23.3069 |
| 0.0503 | 1.0913 | 11000 | 0.1261 | 24.1885 | 21.9946 |
| 0.0363 | 1.1905 | 12000 | 0.1212 | 23.0877 | 21.0642 |
| 0.0562 | 1.2897 | 13000 | 0.1177 | 22.5090 | 20.7266 |
| 0.0382 | 1.3889 | 14000 | 0.1152 | 21.6053 | 19.8785 |
| 0.0457 | 1.4881 | 15000 | 0.1143 | 21.0224 | 19.4502 |
| 0.0394 | 1.5873 | 16000 | 0.1072 | 20.3892 | 18.8130 |
| 0.0427 | 1.6865 | 17000 | 0.1066 | 19.8482 | 18.2814 |
| 0.03 | 1.7857 | 18000 | 0.1033 | 19.0619 | 17.5957 |
| 0.0311 | 1.8849 | 19000 | 0.1018 | 18.7390 | 17.2391 |
| 0.0308 | 1.9841 | 20000 | 0.1004 | 18.8753 | 17.3172 |
| 0.0297 | 2.0833 | 21000 | 0.1034 | 18.1309 | 16.7623 |
| 0.0158 | 2.1825 | 22000 | 0.1052 | 18.5042 | 17.1463 |
| 0.0157 | 2.2817 | 23000 | 0.1039 | 17.8290 | 16.4374 |
| 0.0367 | 2.3810 | 24000 | 0.1022 | 18.0953 | 16.8129 |
| 0.0144 | 2.4802 | 25000 | 0.1041 | 17.3551 | 16.0724 |
| 0.01 | 2.5794 | 26000 | 0.1051 | 17.3132 | 15.9880 |
| 0.0116 | 2.6786 | 27000 | 0.1046 | 16.8561 | 15.4711 |
| 0.0149 | 2.7778 | 28000 | 0.1011 | 16.9861 | 15.5914 |
| 0.02 | 2.8770 | 29000 | 0.1008 | 16.4367 | 15.1357 |
| 0.0122 | 2.9762 | 30000 | 0.1002 | 16.1914 | 14.9352 |
| 0.004 | 3.0754 | 31000 | 0.1057 | 15.6861 | 14.3403 |
| 0.0055 | 3.1746 | 32000 | 0.1067 | 15.7783 | 14.4795 |
| 0.0045 | 3.2738 | 33000 | 0.1089 | 15.7133 | 14.3761 |
| 0.0084 | 3.3730 | 34000 | 0.1072 | 15.7196 | 14.4500 |
| 0.0046 | 3.4722 | 35000 | 0.1087 | 15.7825 | 14.4837 |
| 0.0032 | 3.5714 | 36000 | 0.1094 | 15.3757 | 14.1567 |
| 0.0085 | 3.6706 | 37000 | 0.1071 | 15.4303 | 14.1989 |
| 0.0064 | 3.7698 | 38000 | 0.1106 | 15.2688 | 14.0280 |
| 0.0037 | 3.8690 | 39000 | 0.1086 | 14.9836 | 13.7263 |
| 0.0123 | 3.9683 | 40000 | 0.1109 | 14.7886 | 13.5639 |
| 0.0021 | 4.0675 | 41000 | 0.1135 | 14.7362 | 13.4900 |
| 0.0017 | 4.1667 | 42000 | 0.1142 | 14.5685 | 13.3402 |
| 0.0019 | 4.2659 | 43000 | 0.1144 | 14.6964 | 13.4141 |
| 0.0013 | 4.3651 | 44000 | 0.1156 | 14.6796 | 13.4225 |
| 0.0051 | 4.4643 | 45000 | 0.1155 | 14.5769 | 13.3381 |
| 0.001 | 4.5635 | 46000 | 0.1162 | 14.4846 | 13.2727 |
| 0.0008 | 4.6627 | 47000 | 0.1170 | 14.5119 | 13.3086 |
| 0.0045 | 4.7619 | 48000 | 0.1149 | 14.6083 | 13.4098 |
| 0.0012 | 4.8611 | 49000 | 0.1164 | 14.3609 | 13.1672 |
| 0.0007 | 4.9603 | 50000 | 0.1166 | 14.4007 | 13.1989 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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