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End of training
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metadata
language:
  - tr
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: 'Whisper Small Tr '
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.1
          type: mozilla-foundation/common_voice_16_1
          config: tr
          split: None
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 18.987030332852974

Whisper Small Tr

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2550
  • Wer: 18.9870

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: 64
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.954 1.46 500 0.2702 20.1768
0.143 2.92 1000 0.2550 18.9870

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2