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metadata
library_name: transformers
language:
  - en
license: mit
base_model: distil-whisper/distil-large-v3
tags:
  - generated_from_trainer
datasets:
  - Jenalea/www_call_center_en_merged
metrics:
  - wer
model-index:
  - name: Distill Whisper Call Center
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: www_call_center_eng_merged
          type: Jenalea/www_call_center_en_merged
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 15.436723341258803

Distill Whisper Call Center

This model is a fine-tuned version of distil-whisper/distil-large-v3 on the www_call_center_eng_merged dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6325
  • Wer: 15.4367

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1595 3.0628 1000 0.3259 14.9904
0.0579 6.1256 2000 0.4136 15.3033
0.0121 9.1884 3000 0.5519 15.2943
0.0021 12.2511 4000 0.6325 15.4367

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.6.0+cu124
  • Datasets 3.4.0
  • Tokenizers 0.20.3