README.md

metadata

language:
  - nl
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - synthesized_accented_data
metrics:
  - wer
model-index:
  - name: Whisper Small NL - bncay0
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Custom Common Voice Dutch
          type: synthesized_accented_data
          args: 'config: nl, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0

Whisper Small NL - bncay0

This model is a fine-tuned version of openai/whisper-small on the Custom Common Voice Dutch dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001
• 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: 3e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 3000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0	47.6190	2000	0.0001	0.0

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.1+cpu
• Datasets 2.20.0
• Tokenizers 0.19.1