readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: openai/whisper-large
    results: []
  ---
  
  <!-- 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. -->
  
  # openai/whisper-large
  
  This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6750
  - Wer: 16.9811
  
  ## 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: 4
  - eval_batch_size: 2
  - 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: 500
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1978        | 2.01  | 100  | 0.5474          | 21.0692 |
  | 0.0087        | 4.02  | 200  | 0.6202          | 19.4969 |
  | 0.0029        | 6.04  | 300  | 0.6264          | 18.2390 |
  | 0.0003        | 8.05  | 400  | 0.6659          | 17.1908 |
  | 0.0002        | 10.06 | 500  | 0.6750          | 16.9811 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  