metadata

language:
  - nl
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper small nl last, Berb2000-GPU
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: nl
          split: test
          args: 'config: nl, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 307.7064764692038

Whisper small nl last, Berb2000-GPU

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1789
Wer: 307.7065

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: 8
seed: 42
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
0.151	0.39	1000	0.2196	89.8038
0.1237	0.78	2000	0.1978	46.0495
0.044	1.17	3000	0.1840	114.0796
0.0385	1.56	4000	0.1789	307.7065

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2