readme: ---
  language:
  - ga
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: whisper-large-v2-Irish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: ga-IE
        split: test
        args: ga-IE
      metrics:
      - name: Wer
        type: wer
        value: 34.26248548199768
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: FLEURS
        type: mozilla-foundation/common_voice_11_0
      metrics:
      - name: Wer
        type: wer
        value: 
  ---
  
  <!-- 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-large-v2-Irish
  
  This model is a fine-tuned version of [kpriyanshu256/whisper-large-v2-cy-500-32-1e-05](https://huggingface.co/kpriyanshu256/whisper-large-v2-cy-500-32-1e-05) on the Common Voice 11.0 and the FLEURS datasets.
  It achieves the following results on the evaluation set:
  - Loss: 0.7879
  - Wer: 34.2625
  
  ## 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: 8
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - 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: 50
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3768        | 0.25  | 250  | 0.7143          | 39.4890 |
  | 0.1498        | 1.15  | 500  | 0.7663          | 35.8014 |
  | 0.0907        | 2.05  | 750  | 0.7730          | 35.2497 |
  | 0.045         | 2.3   | 1000 | 0.7879          | 34.2625 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  