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: 0.4378
- Wer: 19.2034
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 |
|---|---|---|---|---|
| 0.7537 | 0.55 | 30 | 0.4344 | 40.1612 |
| 0.3924 | 1.09 | 60 | 0.3993 | 40.9199 |
| 0.2148 | 1.64 | 90 | 0.3921 | 22.2538 |
| 0.1731 | 2.18 | 120 | 0.4108 | 21.7955 |
| 0.0933 | 2.73 | 150 | 0.3953 | 20.7523 |
| 0.0682 | 3.27 | 180 | 0.4179 | 17.2594 |
| 0.0377 | 3.82 | 210 | 0.4136 | 17.3226 |
| 0.0227 | 4.36 | 240 | 0.4298 | 20.0411 |
| 0.0137 | 4.91 | 270 | 0.4378 | 19.2034 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0