Quentin Meeus
training 1600 steps slue-voxpopuli combined labels
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metadata
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - qmeeus/slue-voxpopuli
metrics:
  - wer
model-index:
  - name: WhisperForNamedEntityRecognition
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: qmeeus/slue-voxpopuli
          type: qmeeus/slue-voxpopuli
          split: dev
        metrics:
          - name: Wer
            type: wer
            value: 10.482824557809192

WhisperForNamedEntityRecognition

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

  • Loss: 8.1514
  • Wer: 10.4828

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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: 200
  • training_steps: 1600
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
31.3741 0.06 100 25.8582 10.4828
13.0078 1.03 200 13.4173 10.4828
10.3619 1.09 300 10.8540 10.4828
8.7869 2.06 400 9.6249 10.4828
7.3964 3.02 500 9.1812 10.4828
6.6321 3.08 600 8.6536 10.4828
6.4612 4.05 700 8.6046 10.4828
4.8358 5.02 800 8.0890 10.4828
4.4918 5.08 900 8.3141 10.4828
4.7548 6.04 1000 8.1660 10.4828
3.7881 7.01 1100 8.2471 10.4828
3.1916 7.07 1200 8.0779 10.4828
3.2039 8.04 1300 8.1106 10.4828
3.038 9.0 1400 8.0875 10.4828
2.3249 9.07 1500 8.1025 10.4828
2.6124 10.03 1600 8.1514 10.4828

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.10.0
  • Datasets 2.7.1.dev0
  • Tokenizers 0.11.0