readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - luigisaetta/atco2_normalized_augmented
  metrics:
  - wer
  model-index:
  - name: whisper-atco2-medium
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: luigisaetta/atco2_normalized_augmented
        type: luigisaetta/atco2_normalized_augmented
        config: en
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 17.50524109014675
  ---
  
  <!-- 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-atco2-medium
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the luigisaetta/atco2_normalized_augmented dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6129
  - Wer: 17.5052
  
  ## 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: 2
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 16
  - 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: 500
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 2.3939        | 1.06  | 50   | 1.8493          | 66.5618 |
  | 0.5127        | 2.13  | 100  | 0.5119          | 30.6080 |
  | 0.0626        | 3.19  | 150  | 0.5410          | 20.4403 |
  | 0.0157        | 4.25  | 200  | 0.5775          | 19.8113 |
  | 0.0107        | 5.32  | 250  | 0.5552          | 19.7065 |
  | 0.0044        | 6.38  | 300  | 0.5723          | 18.1342 |
  | 0.0013        | 7.45  | 350  | 0.5763          | 17.7149 |
  | 0.0005        | 8.51  | 400  | 0.6053          | 17.7149 |
  | 0.0004        | 9.57  | 450  | 0.6109          | 17.5052 |
  | 0.0004        | 10.64 | 500  | 0.6129          | 17.5052 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.11.0
  