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: 0.2572
- Wer: 9.3873
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 |
|---|---|---|---|---|
| 0.5724 | 0.49 | 30 | 0.2638 | 10.5041 |
| 0.2659 | 0.98 | 60 | 0.2264 | 9.9205 |
| 0.1374 | 1.48 | 90 | 0.2247 | 9.6992 |
| 0.1421 | 1.97 | 120 | 0.2209 | 10.2626 |
| 0.0576 | 2.46 | 150 | 0.2297 | 9.8098 |
| 0.056 | 2.95 | 180 | 0.2269 | 8.8138 |
| 0.0276 | 3.44 | 210 | 0.2474 | 10.0916 |
| 0.02 | 3.93 | 240 | 0.2427 | 9.4275 |
| 0.0108 | 4.43 | 270 | 0.2527 | 9.4879 |
| 0.0077 | 4.92 | 300 | 0.2572 | 9.3873 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0