whisper_l2_to_cv_sq / README.md
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metadata
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - rishabhjain16/owr_cv_albanian
metrics:
  - wer
model-index:
  - name: Whisper large V2 to CV Albanian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: rishabhjain16/owr_cv_albanian default
          type: rishabhjain16/owr_cv_albanian
        metrics:
          - name: Wer
            type: wer
            value: 34.623217922606926

Whisper large V2 to CV Albanian

This model is a fine-tuned version of openai/whisper-large-v2 on the rishabhjain16/owr_cv_albanian default dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7918
  • Wer: 34.6232

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0515 9.0 500 0.6733 42.4847
0.0101 18.01 1000 0.6810 37.5967
0.0074 27.01 1500 0.7185 38.0855
0.0009 37.0 2000 0.6987 35.5193
0.0002 46.0 2500 0.7393 35.0305
0.0001 55.01 3000 0.7603 35.0305
0.0001 64.01 3500 0.7739 34.8676
0.0001 74.0 4000 0.7832 34.8269
0.0001 83.0 4500 0.7895 34.9084
0.0001 92.01 5000 0.7918 34.6232

Framework versions

  • Transformers 4.37.2
  • Pytorch 1.14.0a0+44dac51
  • Datasets 2.17.1
  • Tokenizers 0.15.2