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Wav2Vec2-Urdu-300M
syedmuhammad/Wav2Vec2-Urdu-300M
Wav2Vec2-Urdu-300M is a automatic speech recognition model from syedmuhammad. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Nov 6, 2023
- Updated
- Nov 11, 2023
- SHA
- 661092aa
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
Wav2Vec2-Urdu-300M
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.3825
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: 0.0003
- 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: 500
- num_epochs: 14
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9658 | 2.58 | 1200 | inf | 0.5573 |
| 0.5669 | 5.17 | 2400 | inf | 0.4473 |
| 0.4117 | 7.75 | 3600 | inf | 0.4121 |
| 0.3197 | 10.33 | 4800 | inf | 0.4039 |
| 0.2667 | 12.92 | 6000 | inf | 0.3825 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Nov 6, 2023
- Updated
- Nov 11, 2023