readme: ---
  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
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # WhisperForNamedEntityRecognition
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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
  