whisper-small-te / README.md
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metadata
language:
  - te
base_model: openai/whisper-small-te
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper small Te sample - Prajwal Nagaraj
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: te
          split: None
          args: 'config: te, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 87.36263736263736

Whisper small Te sample - Prajwal Nagaraj

This model is a fine-tuned version of openai/whisper-small-te on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7139
  • Wer: 87.3626

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0001 71.4286 500 0.7139 87.3626

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1