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whisper-tiny-ta

Automatic Speech Recognition
Transformers
PyTorch
Tamil
whisper
whisper-event
generated_from_trainer
Eval Results
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metadata
language:
  - ta
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Tiny Ta - Bharat Ramanathan
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: ta
          split: test
          args: ta
        metrics:
          - type: wer
            value: 30.102694404742998
            name: Wer
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ta_in
          split: test
        metrics:
          - type: wer
            value: 26.07
            name: WER

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