README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - whisper-event
metrics:
  - wer
model-index:
  - name: agnesluhtaru/whisper-medium-et
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: et
          split: test
        metrics:
          - type: wer
            value: 28.6
            name: WER

whisper-small-et

This model is a fine-tuned version of openai/whisper-medium on the following datasets: Common Voice 11, VoxPopuli and FLEURS.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Estonian data from Common Voice 11, VoxPopuli and FLEURS corpora as both training and validation sets. Tested on Common Voice 11 test set.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• 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: 5000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.12.1+rocm5.1.1
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2