readme: ---
  language:
  - lv
  license: apache-2.0
  tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Large-v2 Latvian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 lv
        type: mozilla-foundation/common_voice_11_0
        config: lv
        split: test
        args: lv
      metrics:
      - name: Wer
        type: wer
        value: 19.97153700189753
  ---
  
  <!-- 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 Latvian
  
  This model is a fine-tuned version of [p4b/whisper-large-v2-lv](https://huggingface.co/p4b/whisper-large-v2-lv) on the mozilla-foundation/common_voice_11_0 lv dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2593
  - Wer: 19.9715
  
  ## 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-07
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 100
  - training_steps: 900
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.7919        | 3.03  | 200  | 0.2793          | 22.5806 |
  | 0.4409        | 6.05  | 400  | 0.2651          | 20.6072 |
  | 0.4393        | 10.01 | 600  | 0.2600          | 20.0664 |
  | 0.4975        | 13.04 | 800  | 0.2593          | 19.9715 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221218+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  