README.md

metadata

language:
  - nl
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Base NL
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13.0
          type: mozilla-foundation/common_voice_13_0
          config: nl
          split: test
          args: 'config: nl, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 20.481842943724686

Whisper Base NL

This model is a fine-tuned version of openai/whisper-base on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3354
• Wer: 20.4818

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
0.294	0.3734	1000	0.4016	24.5123
0.216	0.7468	2000	0.3617	22.3141
0.1437	1.1202	3000	0.3424	21.1733
0.1299	1.4937	4000	0.3354	20.4818

Framework versions

• Transformers 4.42.0.dev0
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1