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whisper-urdu-pytorch
mahwizzzz/whisper-urdu-pytorch
whisper-urdu-pytorch is a machine learning model from mahwizzzz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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Updated Aug 11, 2025
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3.5 GB
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At a glance
- License
- mit
- Access
- Public
- Created
- Aug 11, 2025
- Updated
- Aug 11, 2025
- SHA
- 19230a68
Model card
From the Hugging Face model README
Urdu Whisper model in Pytorch from scratch implementation
Trained a small Urdu whisper model
Robust Speech Recognition via Large-Scale Weak Supervision
ModelArgs Hyperparameters
| Parameter | Value | Description |
|---|---|---|
batch_size | 128 | The number of samples processed before the model is updated. |
max_lr | 1.5e-3 | Maximum learning rate. |
dropout | 0.1 | Dropout rate for regularization. |
epochs | 2 | Number of training epochs. |
block_size | 64 | Sequence length (number of tokens or time steps). |
tgt_vocab_size | 200024 | Size of the target vocabulary. |
embeddings_dims | 512 | Dimensionality of token embeddings. |
attn_dropout | 0.1 | Dropout rate for attention layers. |
no_of_heads | 4 | Number of attention heads in multi-head attention. |
no_of_decoder_layers | 6 | Number of decoder layers in the model. |
weight_decay_optim | 0.1 | Weight decay for the optimizer. |
log_mel_features | 80 | Number of Mel spectrogram features. |
kernel_size | 3 | Kernel size for convolutional layers. |
stride | 2 | Stride for convolutional layers. |
sr | 16000 | Sampling rate of the audio. |
device | 'cuda:0' | Device to run the model on (e.g., GPU). |
SAMPLING_RATE | 16000 | Sampling rate of the audio. |
N_MELS | 80 | Number of Mel bins in the spectrogram. |
WINDOW_DURATION | 0.025 | Duration of the analysis window in seconds (25 ms). |
STRIDE_DURATION | 0.010 | Stride between consecutive windows in seconds (10 ms). |
max_t | 500 | Maximum time steps in the spectrogram. |
n_channels | 80 | Number of channels in the input spectrogram. |
Dataset
Used the 'xs' snapshot.
Frameworks:
Pytorch
Epochs/Steps
Epochs (train) = 2
Val iterations = every epoch
Loss Curves
- License
- mit
- Languages
- ur
- Created
- Aug 11, 2025
- Updated
- Aug 11, 2025