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: 0.1620
- Wer: 5.3772
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 |
|---|---|---|---|---|
| 0.42 | 0.38 | 30 | 0.1892 | 7.8607 |
| 0.1804 | 0.75 | 60 | 0.1588 | 7.0793 |
| 0.1293 | 1.12 | 90 | 0.1579 | 6.9632 |
| 0.075 | 1.5 | 120 | 0.1520 | 6.4371 |
| 0.0734 | 1.88 | 150 | 0.1482 | 5.9961 |
| 0.05 | 2.25 | 180 | 0.1534 | 5.6480 |
| 0.0299 | 2.62 | 210 | 0.1534 | 5.5629 |
| 0.0332 | 3.0 | 240 | 0.1480 | 5.6712 |
| 0.0157 | 3.38 | 270 | 0.1506 | 5.3694 |
| 0.0148 | 3.75 | 300 | 0.1563 | 5.3772 |
| 0.0113 | 4.12 | 330 | 0.1578 | 5.2998 |
| 0.0073 | 4.5 | 360 | 0.1633 | 5.2611 |
| 0.007 | 4.88 | 390 | 0.1620 | 5.3772 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0