metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- kul-speech-lab/CGN
metrics:
- wer
model-index:
- name: Whisper Small CGN
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: kul-speech-lab/CGN
type: kul-speech-lab/CGN
config: cgn-dev.py
split: test
metrics:
- name: Wer
type: wer
value: 15.197170132057957
Whisper Small CGN
This model is a fine-tuned version of openai/whisper-small on the kul-speech-lab/CGN dataset. It achieves the following results on the evaluation set:
- Loss: 0.3386
- Wer: 15.1972
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1967 | 1.01 | 1000 | 0.4085 | 21.8459 |
| 0.1355 | 2.03 | 2000 | 0.3752 | 18.6212 |
| 0.2952 | 3.04 | 3000 | 0.3535 | 18.5841 |
| 0.1876 | 4.05 | 4000 | 0.3464 | 17.5097 |
| 0.1037 | 6.01 | 5000 | 0.3396 | 16.7360 |
| 0.0473 | 7.02 | 6000 | 0.3526 | 16.4131 |
| 0.1605 | 8.04 | 7000 | 0.3284 | 16.4012 |
| 0.0537 | 9.05 | 8000 | 0.3386 | 15.9454 |
| 0.0928 | 11.01 | 9000 | 0.3315 | 15.9568 |
| 0.0144 | 12.02 | 10000 | 0.3532 | 15.5387 |
| 0.0267 | 13.04 | 11000 | 0.3261 | 15.7577 |
| 0.0936 | 14.05 | 12000 | 0.3155 | 15.3380 |
| 0.0825 | 16.01 | 13000 | 0.3198 | 15.2653 |
| 0.0498 | 17.02 | 14000 | 0.3386 | 15.1972 |
| 0.0338 | 18.03 | 15000 | 0.3413 | 15.1972 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
Whisper small model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN).