wav2vec2-large-xlsr-53-ur-cv13
This model is a fine-tuned version of Talha/URDU-ASR on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4323
- Wer: 0.3988
- Cer: 0.1932
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.8043 | 1.46 | 250 | 0.5256 | 0.4023 | 0.1949 |
| 0.5435 | 2.92 | 500 | 0.4381 | 0.3965 | 0.1961 |
| 0.4827 | 4.39 | 750 | 0.4323 | 0.3988 | 0.1932 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
Talha/URDU-ASR