readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - audiofolder
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Bambara Fieldwork
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: audiofolder
        type: audiofolder
        config: default
        split: train
        args: default
      metrics:
      - name: Wer
        type: wer
        value: 157.60036917397323
  ---
  
  <!-- 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. -->
  
  # Whisper Medium Bambara Fieldwork
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.0725
  - Wer: 157.6004
  
  ## 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: 2
  - seed: 42
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 13532
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer      |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.6342        | 1.03  | 1000  | 2.5810          | 159.5293 |
  | 0.2873        | 3.03  | 2000  | 2.9513          | 159.1140 |
  | 0.1461        | 5.02  | 3000  | 3.6833          | 158.3941 |
  | 0.049         | 7.02  | 4000  | 4.0725          | 157.6004 |
  | 0.0218        | 9.01  | 5000  | 4.2531          | 158.3664 |
  | 0.0071        | 11.0  | 6000  | 4.5944          | 157.9972 |
  | 0.0057        | 12.04 | 7000  | 4.6659          | 161.4952 |
  | 0.0061        | 14.03 | 8000  | 4.9162          | 161.0614 |
  | 0.0042        | 16.03 | 9000  | 5.0205          | 158.9848 |
  | 0.0007        | 18.02 | 10000 | 5.1463          | 159.1970 |
  | 0.0015        | 20.01 | 11000 | 5.2150          | 159.0401 |
  | 0.0001        | 22.01 | 12000 | 5.3008          | 159.5478 |
  | 0.0001        | 24.0  | 13000 | 5.3800          | 159.0309 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  