README.md

metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
language:
  - hu
widget:
  - example_title: Sample 1
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
  - example_title: Sample 2
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
metrics:
  - wer
pipeline_tag: automatic-speech-recognition
model-index:
  - name: Whisper Tiny Hungarian v11 - cleaned
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.1 - Hungarian
          type: mozilla-foundation/common_voice_16_1
          config: hu
          split: test
          args: hu
        metrics:
          - name: Wer
            type: wer
            value: null

Whisper Tiny Hu v11 - cleaned

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.1 hu cleaned dataset. It achieves the following results on the evaluation set:

• Loss: 0.2233
• Wer Ortho: 19.1444
• Wer: 18.1201

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: 4e-05
• train_batch_size: 64
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 100
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.002	3.32	1000	0.2233	19.1444	18.1201

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.1