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whisper-largev3-paraspeak-v2

Automatic Speech Recognition
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metadata
language:
  - hi
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - pranetk/paraspeak-data-v3
metrics:
  - wer
model-index:
  - name: Whisper Large V3 Paraspeak V2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Paraspeak Dataset 3.0
          type: pranetk/paraspeak-data-v3
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 62.121212121212125

Whisper Large V3 Paraspeak V2

This model is a fine-tuned version of openai/whisper-large-v3 on the Paraspeak Dataset 3.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0662
  • Wer: 62.1212

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1361 2.9412 50 0.8743 77.2727
0.0603 5.8824 100 1.0115 65.1515
0.0452 8.8235 150 1.0837 71.2121
0.0042 11.7647 200 1.0400 78.7879
0.023 14.7059 250 1.0296 71.2121
0.0023 17.6471 300 0.9761 69.6970
0.0005 20.5882 350 1.0758 71.2121
0.0098 23.5294 400 1.1036 71.2121
0.0006 26.4706 450 1.0662 65.1515
0.0001 29.4118 500 1.0563 62.1212
0.0 32.3529 550 1.0521 62.1212
0.0 35.2941 600 1.0541 62.1212
0.0 38.2353 650 1.0563 62.1212
0.0 41.1765 700 1.0587 62.1212
0.0 44.1176 750 1.0609 62.1212
0.0 47.0588 800 1.0628 62.1212
0.0 50.0 850 1.0641 62.1212
0.0 52.9412 900 1.0653 62.1212
0.0 55.8824 950 1.0659 62.1212
0.0 58.8235 1000 1.0662 62.1212

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1