File size: 3,010 Bytes
64b637d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | ---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny AR - BH
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 tiny AR - BH
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0244
- Wer: 0.1485
- Cer: 0.0491
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0508 | 1.0 | 157 | 0.0447 | 2.1609 | 0.9033 |
| 0.0294 | 2.0 | 314 | 0.0286 | 1.9660 | 1.0025 |
| 0.0226 | 3.0 | 471 | 0.0254 | 0.4391 | 0.1838 |
| 0.0147 | 4.0 | 628 | 0.0224 | 0.3542 | 0.1358 |
| 0.0129 | 5.0 | 785 | 0.0213 | 0.5243 | 0.2350 |
| 0.0091 | 6.0 | 942 | 0.0199 | 0.3001 | 0.1045 |
| 0.0065 | 7.0 | 1099 | 0.0196 | 0.2268 | 0.0728 |
| 0.0043 | 8.0 | 1256 | 0.0196 | 0.2011 | 0.0645 |
| 0.003 | 9.0 | 1413 | 0.0201 | 0.2885 | 0.1164 |
| 0.003 | 10.0 | 1570 | 0.0209 | 0.3251 | 0.1150 |
| 0.0016 | 11.0 | 1727 | 0.0207 | 0.1828 | 0.0607 |
| 0.0009 | 12.0 | 1884 | 0.0209 | 0.1747 | 0.0537 |
| 0.0007 | 13.0 | 2041 | 0.0211 | 0.1680 | 0.0517 |
| 0.0005 | 14.0 | 2198 | 0.0218 | 0.1652 | 0.0504 |
| 0.0003 | 15.0 | 2355 | 0.0211 | 0.1580 | 0.0496 |
| 0.0002 | 16.0 | 2512 | 0.0216 | 0.1566 | 0.0487 |
| 0.0001 | 17.0 | 2669 | 0.0224 | 0.1562 | 0.0492 |
| 0.0 | 18.0 | 2826 | 0.0227 | 0.1481 | 0.0454 |
| 0.0 | 19.0 | 2983 | 0.0239 | 0.1471 | 0.0489 |
| 0.0 | 19.8768 | 3120 | 0.0237 | 0.1461 | 0.0462 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|