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: 0.3679
- Wer: 12.7848
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 |
|---|---|---|---|---|
| 0.7686 | 0.55 | 30 | 0.3602 | 18.3326 |
| 0.3835 | 1.09 | 60 | 0.3292 | 15.3107 |
| 0.22 | 1.64 | 90 | 0.3163 | 16.9069 |
| 0.1668 | 2.18 | 120 | 0.3356 | 16.5194 |
| 0.0955 | 2.73 | 150 | 0.3383 | 13.4356 |
| 0.0674 | 3.27 | 180 | 0.3632 | 11.9944 |
| 0.0376 | 3.82 | 210 | 0.3584 | 12.6143 |
| 0.0218 | 4.36 | 240 | 0.3645 | 12.9242 |
| 0.0136 | 4.91 | 270 | 0.3679 | 12.7848 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0