metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small Dutch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: data/copas copas-full
type: data/copas
config: copas-full
split: test
args: copas-full
metrics:
- name: Wer
type: wer
value: 0
Whisper Small Dutch
This model is a fine-tuned version of qmeeus/whisper-small-nl on the data/copas copas-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.0015
- Wer: 0.0
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1291 | 2.03 | 500 | 0.2953 | 25.0681 |
| 0.0524 | 5.03 | 1000 | 0.1626 | 13.9118 |
| 0.0403 | 8.03 | 1500 | 0.0825 | 6.5450 |
| 0.0349 | 11.03 | 2000 | 0.0409 | 2.5652 |
| 0.0122 | 14.03 | 2500 | 0.0173 | 0.6619 |
| 0.0053 | 17.03 | 3000 | 0.0068 | 0.0822 |
| 0.0032 | 20.02 | 3500 | 0.0037 | 0.0173 |
| 0.0022 | 23.02 | 4000 | 0.0024 | 0.0 |
| 0.0018 | 26.02 | 4500 | 0.0018 | 0.0 |
| 0.0016 | 29.02 | 5000 | 0.0015 | 0.0 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1