Whisper large fa - marziye-A
This model is a fine-tuned version of openai/whisper-large on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1571
- Wer: 19.7418
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2189 | 0.1567 | 2000 | 0.2248 | 29.0575 |
| 0.1972 | 0.3134 | 4000 | 0.2035 | 25.1376 |
| 0.1906 | 0.4701 | 6000 | 0.1923 | 25.7159 |
| 0.1595 | 0.6268 | 8000 | 0.1806 | 22.4166 |
| 0.1747 | 0.7835 | 10000 | 0.1753 | 23.0041 |
| 0.1744 | 0.9402 | 12000 | 0.1709 | 22.4932 |
| 0.1357 | 1.0969 | 14000 | 0.1687 | 20.7782 |
| 0.1345 | 1.2536 | 16000 | 0.1646 | 21.3221 |
| 0.1362 | 1.4103 | 18000 | 0.1619 | 21.1082 |
| 0.121 | 1.5670 | 20000 | 0.1601 | 20.3781 |
| 0.1354 | 1.7237 | 22000 | 0.1587 | 19.8157 |
| 0.122 | 1.8804 | 24000 | 0.1571 | 19.7418 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for marziye-A/whisper-large-v3-full-youtube_80hour_7
Base model
openai/whisper-large