readme: ---
  language:
  - mn
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mn
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: sammy786/wav2vec2-xlsr-mongolian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: mn
      metrics:
      - name: Test WER
        type: wer
        value: 32.63
      - name: Test CER
        type: cer
        value: 9.26
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: mn
      metrics:
      - name: Test WER
        type: wer
        value: 91.26
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: mn
      metrics:
      - name: Test WER
        type: wer
        value: 91.37
  ---
  # sammy786/wav2vec2-xlsr-mongolian
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - mn dataset.
  It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
  - Loss: 31.52
  - Wer: 34.1522
  ## Model description
  "facebook/wav2vec2-xls-r-1b" was finetuned.
  ## Intended uses & limitations
  More information needed
  ## Training and evaluation data
  Training data - 
  Common voice Finnish train.tsv, dev.tsv and other.tsv
  ## Training procedure
  For creating the train dataset, all possible datasets were appended and 90-10 split was used. 
  ### Training hyperparameters
  The following hyperparameters were used during training:
  - learning_rate: 0.000045637994662983496
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 13
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine_with_restarts
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  | Step | Training Loss | Validation Loss | Wer      |
  |:----:|:-------------:|:---------------:|:--------:|
  | 200  | 4.906200      | 3.012986        | 1.000000 |
  | 400  | 1.734600      | 0.704821        | 0.750497 |
  | 600  | 1.132100      | 0.496223        | 0.531241 |
  | 800  | 0.929300      | 0.468937        | 0.469043 |
  | 1000 | 0.772300      | 0.425313        | 0.448168 |
  | 1200 | 0.623900      | 0.394633        | 0.414229 |
  | 1400 | 0.512400      | 0.369225        | 0.397614 |
  | 1600 | 0.439900      | 0.346033        | 0.391650 |
  | 1800 | 0.391300      | 0.358454        | 0.379296 |
  | 2000 | 0.377000      | 0.346822        | 0.359415 |
  | 2200 | 0.347500      | 0.325205        | 0.348481 |
  | 2400 | 0.343600      | 0.315233        | 0.344078 |
  | 2600 | 0.328000      | 0.308826        | 0.341522 |
  | 2800 | 0.358200      | 0.331786        | 0.343084 |
  | 3000 | 0.417200      | 0.370051        | 0.356433 |
  | 3200 | 0.685300      | 0.595438        | 0.407413 |
  | 3400 | 0.764100      | 0.643449        | 0.359983 |
  | 3600 | 0.717100      | 0.505033        | 0.371911 |
  | 3800 | 0.620900      | 0.464138        | 0.369071 |
  | 4000 | 0.590700      | 0.445417        | 0.363249 |
  | 4200 | 0.561000      | 0.440727        | 0.360267 |
  | 4400 | 0.550600      | 0.447122        | 0.360267 |
  | 4600 | 0.562100      | 0.457020        | 0.359841 |
  | 4800 | 0.578800      | 0.470477        | 0.360551 |
  | 5000 | 0.580400      | 0.481413        | 0.362539 |
  | 5200 | 0.605500      | 0.485240        | 0.362823 |
  | 5400 | 0.582900      | 0.486654        | 0.362965 |
  | 5600 | 0.593900      | 0.486715        | 0.363107 |
  | 5800 | 0.590900      | 0.486716        | 0.363107 |
  | 6000 | 0.587200      | 0.486716        | 0.363107 |
  
  
  ### Framework versions
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.0+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  #### Evaluation Commands
  1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
  
  ```bash
  python eval.py --model_id sammy786/wav2vec2-xlsr-mongolian --dataset mozilla-foundation/common_voice_8_0 --config mn --split test
  ```