Whisper Large Ur
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 14.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5744
- Wer: 34.2870
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0134 | 9.07 | 1000 | 0.5744 | 34.2870 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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Model tree for lanmandragoran/urdu-whisper-large-v2-zero-stage-2-bf16
Base model
openai/whisper-large-v2