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---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base AR - BA
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 base AR - BA
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1070
- Wer: 0.2297
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 78.8449 | 1.0 | 313 | 0.1892 | 0.7483 |
| 23.7046 | 2.0 | 626 | 0.1465 | 0.4188 |
| 13.1378 | 3.0 | 939 | 0.1347 | 0.3632 |
| 8.2072 | 4.0 | 1252 | 0.1312 | 0.3285 |
| 5.8166 | 5.0 | 1565 | 0.1316 | 0.2937 |
| 4.5461 | 6.0 | 1878 | 0.1339 | 0.2916 |
| 3.8785 | 7.0 | 2191 | 0.1276 | 0.2838 |
| 3.1975 | 8.0 | 2504 | 0.1253 | 0.2762 |
| 2.8784 | 9.0 | 2817 | 0.1240 | 0.2881 |
| 2.6303 | 10.0 | 3130 | 0.1238 | 0.2719 |
| 2.481 | 11.0 | 3443 | 0.1225 | 0.2670 |
| 2.2994 | 12.0 | 3756 | 0.1221 | 0.2641 |
| 2.0863 | 13.0 | 4069 | 0.1214 | 0.2672 |
| 2.0235 | 14.0 | 4382 | 0.1213 | 0.2638 |
| 2.015 | 14.9536 | 4680 | 0.1213 | 0.2626 |
| 7.0386 | 13.0 | 4875 | 0.1209 | 0.2760 |
| 5.2638 | 14.0 | 5250 | 0.1169 | 0.2538 |
| 3.8581 | 15.0 | 5625 | 0.1180 | 0.2374 |
| 3.4661 | 16.0 | 6000 | 0.1176 | 0.2408 |
| 2.8903 | 17.0 | 6375 | 0.1167 | 0.2359 |
| 2.6081 | 18.0 | 6750 | 0.1172 | 0.2358 |
| 2.6719 | 19.0 | 7125 | 0.1165 | 0.2401 |
| 2.4235 | 20.0 | 7500 | 0.1160 | 0.2430 |
| 4.9497 | 21.0 | 7875 | 0.1133 | 0.2361 |
| 3.6345 | 22.0 | 8250 | 0.1136 | 0.2274 |
| 3.092 | 23.0 | 8625 | 0.1123 | 0.2305 |
| 2.606 | 24.0 | 9000 | 0.1098 | 0.2283 |
| 2.4858 | 25.0 | 9375 | 0.1103 | 0.2253 |
| 2.1898 | 26.0 | 9750 | 0.1109 | 0.2327 |
| 2.1861 | 27.0 | 10125 | 0.1088 | 0.2311 |
| 1.8994 | 28.0 | 10500 | 0.1084 | 0.2261 |
| 1.8208 | 29.0 | 10875 | 0.1078 | 0.2266 |
| 1.706 | 30.0 | 11250 | 0.1077 | 0.2287 |
| 1.5895 | 31.0 | 11625 | 0.1067 | 0.2233 |
| 1.5086 | 32.0 | 12000 | 0.1068 | 0.2299 |
| 1.4744 | 33.0 | 12375 | 0.1065 | 0.2268 |
| 1.4184 | 34.0 | 12750 | 0.1056 | 0.2266 |
| 1.4134 | 35.0 | 13125 | 0.1064 | 0.2331 |
| 1.3246 | 36.0 | 13500 | 0.1054 | 0.2263 |
| 1.3368 | 37.0 | 13875 | 0.1057 | 0.2317 |
| 1.3084 | 38.0 | 14250 | 0.1053 | 0.2412 |
| 1.302 | 39.0 | 14625 | 0.1054 | 0.2309 |
| 1.2152 | 40.0 | 15000 | 0.1053 | 0.2297 |
| 3.6933 | 37.9994 | 15314 | 0.1044 | 0.2122 |
| 2.9938 | 39.0 | 15718 | 0.1051 | 0.2193 |
| 2.5582 | 40.0 | 16122 | 0.1041 | 0.2202 |
| 2.1949 | 41.0 | 16526 | 0.1032 | 0.2137 |
| 2.1428 | 42.0 | 16930 | 0.1045 | 0.2146 |
| 2.0052 | 43.0 | 17334 | 0.1027 | 0.2146 |
| 1.7204 | 44.0 | 17738 | 0.1031 | 0.2121 |
| 1.7391 | 45.0 | 18142 | 0.1026 | 0.2125 |
| 1.6544 | 46.0 | 18546 | 0.1028 | 0.2140 |
| 1.6764 | 47.0 | 18950 | 0.1033 | 0.2121 |
| 1.535 | 48.0 | 19354 | 0.1028 | 0.2122 |
| 1.5344 | 49.0 | 19758 | 0.1025 | 0.2163 |
| 1.5171 | 49.9721 | 20150 | 0.1025 | 0.2121 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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