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: 0.3901
- Wer: 13.6657
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 |
|---|---|---|---|---|
| 0.6756 | 0.71 | 30 | 0.3774 | 15.0287 |
| 0.2704 | 1.43 | 60 | 0.3396 | 13.4864 |
| 0.1792 | 2.14 | 90 | 0.3453 | 12.6793 |
| 0.0815 | 2.86 | 120 | 0.3393 | 17.2704 |
| 0.0432 | 3.57 | 150 | 0.3639 | 14.2217 |
| 0.0249 | 4.29 | 180 | 0.3874 | 14.7418 |
| 0.0132 | 5.0 | 210 | 0.3901 | 13.6657 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0