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: 0.1401
- Wer: 5.5491
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 |
|---|---|---|---|---|
| 0.4119 | 0.38 | 30 | 0.1653 | 7.8245 |
| 0.1737 | 0.75 | 60 | 0.1446 | 5.7271 |
| 0.1437 | 1.12 | 90 | 0.1420 | 6.7487 |
| 0.0785 | 1.5 | 120 | 0.1317 | 5.1931 |
| 0.0707 | 1.88 | 150 | 0.1309 | 6.2379 |
| 0.0496 | 2.25 | 180 | 0.1369 | 5.9670 |
| 0.0318 | 2.62 | 210 | 0.1316 | 6.0367 |
| 0.0341 | 3.0 | 240 | 0.1290 | 5.5568 |
| 0.0166 | 3.38 | 270 | 0.1339 | 4.9532 |
| 0.0147 | 3.75 | 300 | 0.1353 | 5.4949 |
| 0.0109 | 4.12 | 330 | 0.1365 | 5.6342 |
| 0.0072 | 4.5 | 360 | 0.1402 | 5.4640 |
| 0.0071 | 4.88 | 390 | 0.1401 | 5.5491 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0