README.md

metadata

language:
  - nl
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: FIFA_WC22_WINNER_LANGUAGE_MODEL
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: 'null'
          split: None
          args: 'config: nl, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 13.5797

whisper-lt-finetune

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: 0.2550
• Wer: 13.5797

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: 250
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1556	0.97	1000	0.2354	15.2781
0.0709	1.95	2000	0.2336	14.6419
0.0259	2.92	3000	0.2415	14.0186
0.0098	3.89	4000	0.2496	13.7355
0.0056	4.87	5000	0.2550	13.5797

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2