whisper-base-hawrami-transcription
This model is a fine-tuned version of razhan/whisper-base-hawrami on the razhan/DOLMA-speech hawrami dataset. It achieves the following results on the evaluation set:
- Loss: 0.2612
- Wer: 0.4013
- Cer: 0.0856
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.6798 | 1.0 | 80 | 0.5513 | 0.6855 | 0.1788 |
| 0.3095 | 2.0 | 160 | 0.2984 | 0.4486 | 0.0972 |
| 0.2673 | 3.0 | 240 | 0.2676 | 0.4143 | 0.0882 |
| 0.2428 | 4.0 | 320 | 0.2612 | 0.4013 | 0.0856 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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