Whisper Dutch - RTL
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
-
Loss: 0.1790
-
Wer: 37.5081
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: 16
-
eval_batch_size: 16
-
seed: 42
-
gradient_accumulation_steps: 2
-
total_train_batch_size: 32
-
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-
lr_scheduler_type: linear
-
lr_scheduler_warmup_steps: 500
-
training_steps: 4000
-
mixed_precision_training: Native AMP
Training results
|
Training Loss
|
Epoch
|
Step
|
Validation Loss
|
Wer
|
|
0.1238
|
0.78
|
1000
|
0.2017
|
19.8254
|
|
0.0548
|
1.56
|
2000
|
0.1829
|
35.4625
|
|
0.0259
|
2.34
|
3000
|
0.1795
|
43.1853
|
|
0.0131
|
3.12
|
4000
|
0.1790
|
37.5081
|
Framework versions
-
Transformers 4.28.1
-
Pytorch 2.0.0+cu117
-
Datasets 2.12.0
-
Tokenizers 0.13.3