metadata
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large V2
results: []
Whisper Large V2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3814
- Wer: 15.3008
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7638 | 0.55 | 30 | 0.3827 | 17.3062 |
| 0.3938 | 1.09 | 60 | 0.3397 | 15.3166 |
| 0.2143 | 1.64 | 90 | 0.3328 | 18.1115 |
| 0.1706 | 2.18 | 120 | 0.3498 | 13.6902 |
| 0.0938 | 2.73 | 150 | 0.3394 | 14.9534 |
| 0.0738 | 3.27 | 180 | 0.3539 | 15.2061 |
| 0.0406 | 3.82 | 210 | 0.3583 | 15.7903 |
| 0.0239 | 4.36 | 240 | 0.3757 | 15.5850 |
| 0.0141 | 4.91 | 270 | 0.3814 | 15.3008 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0