whisper-large-v3-mici-princ
This model is a fine-tuned version of openai/whisper-large-v3 on the Mići Princ dataset. It achieves the following results on the evaluation set:
- Loss: 1.4596
- Wer: 33.5008
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: 8
- 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: 100
- training_steps: 3090
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0013 | 17.66 | 309 | 1.1495 | 37.1859 |
| 0.0009 | 35.31 | 618 | 1.1700 | 27.3032 |
| 0.0001 | 52.97 | 927 | 1.3428 | 27.7219 |
| 0.0001 | 70.63 | 1236 | 1.3874 | 27.2194 |
| 0.0001 | 88.29 | 1545 | 1.4141 | 27.3869 |
| 0.0001 | 105.94 | 1854 | 1.4331 | 33.5008 |
| 0.0001 | 123.6 | 2163 | 1.4445 | 33.3333 |
| 0.0 | 141.26 | 2472 | 1.4520 | 33.3333 |
| 0.0 | 158.91 | 2781 | 1.4576 | 33.3333 |
| 0.0 | 176.57 | 3090 | 1.4596 | 33.5008 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-large-v3