đ Automatic Speech Recognition Model
This model is a fine - tuned speech recognition model that addresses the challenge of transcribing Urdu speech accurately. It offers high - quality speech - to - text conversion on the Urdu dataset, providing valuable results for related applications.
đ Quick Start
This model is a fine - tuned version of [facebook/wav2vec2 - xls - r - 1b](https://huggingface.co/facebook/wav2vec2 - xls - r - 1b) on the MOZILLA - FOUNDATION/COMMON_VOICE_8_0 - UR dataset.
It achieves the following results on the evaluation set:
đ Documentation
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: 7.5e - 05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
| 5.3118 |
1.96 |
100 |
2.9093 |
0.9982 |
| 2.2071 |
3.92 |
200 |
1.1737 |
0.7779 |
| 1.6098 |
5.88 |
300 |
0.9984 |
0.7015 |
| 1.4333 |
7.84 |
400 |
0.9800 |
0.6705 |
| 1.2859 |
9.8 |
500 |
0.9582 |
0.6487 |
| 1.2073 |
11.76 |
600 |
0.8841 |
0.6077 |
| 1.1417 |
13.73 |
700 |
0.9118 |
0.6343 |
| 1.0988 |
15.69 |
800 |
0.9217 |
0.6196 |
| 1.0279 |
17.65 |
900 |
0.9165 |
0.5867 |
| 0.9765 |
19.61 |
1000 |
0.9306 |
0.5978 |
| 0.9161 |
21.57 |
1100 |
0.9305 |
0.5768 |
| 0.8395 |
23.53 |
1200 |
0.9828 |
0.5819 |
| 0.8306 |
25.49 |
1300 |
0.9397 |
0.5760 |
| 0.7819 |
27.45 |
1400 |
0.9544 |
0.5742 |
| 0.7509 |
29.41 |
1500 |
0.9278 |
0.5690 |
| 0.7218 |
31.37 |
1600 |
0.9003 |
0.5587 |
| 0.6725 |
33.33 |
1700 |
0.9659 |
0.5554 |
| 0.6287 |
35.29 |
1800 |
0.9522 |
0.5561 |
| 0.6077 |
37.25 |
1900 |
0.9154 |
0.5465 |
| 0.5873 |
39.22 |
2000 |
0.9331 |
0.5469 |
| 0.5621 |
41.18 |
2100 |
0.9335 |
0.5491 |
| 0.5168 |
43.14 |
2200 |
0.9632 |
0.5458 |
| 0.5114 |
45.1 |
2300 |
0.9349 |
0.5387 |
| 0.4986 |
47.06 |
2400 |
0.9364 |
0.5380 |
| 0.4761 |
49.02 |
2500 |
0.9584 |
0.5391 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
đ License
This model is licensed under the Apache - 2.0 license.
đ Model Information
| Property |
Details |
| Model Type |
Fine - tuned version of facebook/wav2vec2 - xls - r - 1b |
| Training Data |
MOZILLA - FOUNDATION/COMMON_VOICE_8_0 - UR dataset |
| Evaluation Results |
Loss: 0.9613; Wer: 0.5376 |
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