Whisper Tiny Ta - Bharat Ramanathan

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3096
  • Wer: 30.1027

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: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5622 0.2 1000 0.4460 41.4141
0.4151 0.4 2000 0.3657 35.1390
0.3727 0.6 3000 0.3417 33.1723
0.3519 0.8 4000 0.3252 31.9497
0.3354 1.0 5000 0.3192 31.3997
0.3492 0.1 6000 0.3283 31.6966
0.3229 0.2 7000 0.3211 31.1339
0.3193 0.3 8000 0.3138 30.5161
0.314 0.4 9000 0.3112 30.1832
0.3087 0.5 10000 0.3096 30.1027

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train parambharat/whisper-tiny-ta

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Evaluation results