metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small Maori
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs mi_nz
          type: google/fleurs
          config: mi_nz
          split: test
          args: mi_nz
        metrics:
          - name: Wer
            type: wer
            value: 30.481593707691317

Whisper Small Maori

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

Loss: 0.7756
Wer: 30.4816

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: 64
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2693	7.02	100	0.6741	35.4845
0.0084	15.01	200	0.7756	30.4816
0.0029	23.0	300	0.8154	31.4744
0.002	30.02	400	0.8320	31.3777
0.0017	38.01	500	0.8372	31.5163

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.1.dev0
Tokenizers 0.13.2