readme: ---
  language:
  - ka
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - ka
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Georgian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: ka
      metrics:
      - name: Test WER
        type: wer
        value: 42.09
      - name: Test CER
        type: cer
        value: 8.01
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: ka
      metrics:
      - name: Test WER
        type: wer
        value: 65.32
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: ka
      metrics:
      - name: Test WER
        type: wer
        value: 65.03
  ---
  
  <!-- 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. -->
  
  # wav2vec2-large-xls-r-300m-georgian
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - KA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3666
  - Wer: 0.4211
  
  ## 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: 0.0003
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.8805        | 5.95  | 500  | 0.7547          | 0.8438 |
  | 1.2123        | 11.9  | 1000 | 0.4732          | 0.6542 |
  | 1.0822        | 17.86 | 1500 | 0.4027          | 0.5778 |
  | 0.9938        | 23.81 | 2000 | 0.3847          | 0.5524 |
  | 0.9383        | 29.76 | 2500 | 0.3845          | 0.5204 |
  | 0.8932        | 35.71 | 3000 | 0.3833          | 0.5297 |
  | 0.8495        | 41.67 | 3500 | 0.3759          | 0.5036 |
  | 0.8201        | 47.62 | 4000 | 0.3616          | 0.4859 |
  | 0.7794        | 53.57 | 4500 | 0.3874          | 0.4938 |
  | 0.735         | 59.52 | 5000 | 0.3748          | 0.4782 |
  | 0.7082        | 65.48 | 5500 | 0.3615          | 0.4675 |
  | 0.669         | 71.43 | 6000 | 0.3797          | 0.4601 |
  | 0.6457        | 77.38 | 6500 | 0.3812          | 0.4515 |
  | 0.6098        | 83.33 | 7000 | 0.3660          | 0.4343 |
  | 0.5874        | 89.29 | 7500 | 0.3640          | 0.4257 |
  | 0.5627        | 95.24 | 8000 | 0.3661          | 0.4239 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  