đ Automatic Speech Recognition Model
This model is a fine - tuned speech recognition model that addresses the challenges of transcribing Urdu speech. It offers high - accuracy transcription on the MOZILLA - FOUNDATION/COMMON_VOICE_8_0 - UR dataset, providing valuable support for Urdu language processing.
đ Quick Start
This model is a fine - tuned version of [facebook/wav2vec2 - large - xlsr - 53](https://huggingface.co/facebook/wav2vec2 - large - xlsr - 53) 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 |
| 10.1224 |
1.96 |
100 |
3.5429 |
1.0 |
| 3.2411 |
3.92 |
200 |
3.1786 |
1.0 |
| 3.1283 |
5.88 |
300 |
3.0571 |
1.0 |
| 3.0044 |
7.84 |
400 |
2.9560 |
0.9996 |
| 2.9388 |
9.8 |
500 |
2.8977 |
1.0011 |
| 2.86 |
11.76 |
600 |
2.6944 |
0.9952 |
| 2.5538 |
13.73 |
700 |
2.0967 |
0.9435 |
| 2.1214 |
15.69 |
800 |
1.4816 |
0.8428 |
| 1.8136 |
17.65 |
900 |
1.2459 |
0.8048 |
| 1.6795 |
19.61 |
1000 |
1.1232 |
0.7649 |
| 1.5571 |
21.57 |
1100 |
1.0510 |
0.7432 |
| 1.4975 |
23.53 |
1200 |
1.0298 |
0.6963 |
| 1.4485 |
25.49 |
1300 |
0.9775 |
0.7074 |
| 1.3924 |
27.45 |
1400 |
0.9798 |
0.6956 |
| 1.3604 |
29.41 |
1500 |
0.9345 |
0.7092 |
| 1.3224 |
31.37 |
1600 |
0.9535 |
0.6830 |
| 1.2816 |
33.33 |
1700 |
0.9178 |
0.6679 |
| 1.2623 |
35.29 |
1800 |
0.9249 |
0.6679 |
| 1.2421 |
37.25 |
1900 |
0.9124 |
0.6734 |
| 1.2208 |
39.22 |
2000 |
0.8962 |
0.6664 |
| 1.2145 |
41.18 |
2100 |
0.8903 |
0.6734 |
| 1.1888 |
43.14 |
2200 |
0.8883 |
0.6708 |
| 1.1933 |
45.1 |
2300 |
0.8928 |
0.6723 |
| 1.1838 |
47.06 |
2400 |
0.8868 |
0.6679 |
| 1.1634 |
49.02 |
2500 |
0.8886 |
0.6657 |
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.
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