whisper-small-vi / README.md
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metadata
language:
  - es
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Vi - Shiv Kumar Ganesh
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: vi
          split: test
          args: vi
        metrics:
          - name: Wer
            type: wer
            value: 46.676902829567894

Whisper Small Vi - Shiv Kumar Ganesh

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

  • Loss: 0.7220
  • Wer: 46.6769

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.7433 1.02 100 1.6824 155.0559
0.5929 2.04 200 0.8475 55.5824
0.1188 3.05 300 0.6646 47.2801
0.0672 5.0 400 0.7099 61.3292
0.0317 6.02 500 0.6951 49.9013
0.0169 7.04 600 0.7658 62.8866
0.0089 8.06 700 0.6681 34.2509
0.004 10.01 800 0.6875 43.8364
0.0015 11.03 900 0.7129 46.8195
0.0011 12.04 1000 0.7194 47.4775
0.0011 13.06 1100 0.7217 46.1505
0.001 15.01 1200 0.7220 46.6769

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2