readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-japanese-colab
    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. -->
  
  # wav2vec2-large-xls-r-300m-japanese-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8060
  - Wer: 0.1393
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - 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: 500
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 2.44  | 100  | 3.7830          | 1.0    |
  | No log        | 4.88  | 200  | 2.9520          | 0.9999 |
  | No log        | 7.32  | 300  | 1.1938          | 0.2940 |
  | 3.7558        | 9.76  | 400  | 0.7278          | 0.1977 |
  | 3.7558        | 12.2  | 500  | 0.6456          | 0.1668 |
  | 3.7558        | 14.63 | 600  | 0.6702          | 0.1530 |
  | 3.7558        | 17.07 | 700  | 0.7131          | 0.1568 |
  | 0.2503        | 19.51 | 800  | 0.7277          | 0.1488 |
  | 0.2503        | 21.95 | 900  | 0.7558          | 0.1630 |
  | 0.2503        | 24.39 | 1000 | 0.7611          | 0.1437 |
  | 0.2503        | 26.83 | 1100 | 0.7501          | 0.1426 |
  | 0.1316        | 29.27 | 1200 | 0.7635          | 0.1445 |
  | 0.1316        | 31.71 | 1300 | 0.8348          | 0.1578 |
  | 0.1316        | 34.15 | 1400 | 0.7285          | 0.1545 |
  | 0.1316        | 36.59 | 1500 | 0.7949          | 0.1491 |
  | 0.0974        | 39.02 | 1600 | 0.7706          | 0.1524 |
  | 0.0974        | 41.46 | 1700 | 0.8180          | 0.1432 |
  | 0.0974        | 43.9  | 1800 | 0.7718          | 0.1281 |
  | 0.0974        | 46.34 | 1900 | 0.7915          | 0.1315 |
  | 0.0731        | 48.78 | 2000 | 0.7905          | 0.1337 |
  | 0.0731        | 51.22 | 2100 | 0.8401          | 0.1340 |
  | 0.0731        | 53.66 | 2200 | 0.7810          | 0.1410 |
  | 0.0731        | 56.1  | 2300 | 0.8034          | 0.1418 |
  | 0.0569        | 58.54 | 2400 | 0.8219          | 0.1472 |
  | 0.0569        | 60.98 | 2500 | 0.7661          | 0.1432 |
  | 0.0569        | 63.41 | 2600 | 0.7989          | 0.1442 |
  | 0.0569        | 65.85 | 2700 | 0.8212          | 0.1440 |
  | 0.0456        | 68.29 | 2800 | 0.8029          | 0.1395 |
  | 0.0456        | 70.73 | 2900 | 0.8113          | 0.1425 |
  | 0.0456        | 73.17 | 3000 | 0.8298          | 0.1434 |
  | 0.0456        | 75.61 | 3100 | 0.8131          | 0.1403 |
  | 0.0343        | 78.05 | 3200 | 0.8313          | 0.1415 |
  | 0.0343        | 80.49 | 3300 | 0.8395          | 0.1434 |
  | 0.0343        | 82.93 | 3400 | 0.8048          | 0.1386 |
  | 0.0343        | 85.37 | 3500 | 0.8126          | 0.1393 |
  | 0.026         | 87.8  | 3600 | 0.7933          | 0.1378 |
  | 0.026         | 90.24 | 3700 | 0.8317          | 0.1389 |
  | 0.026         | 92.68 | 3800 | 0.8005          | 0.1378 |
  | 0.026         | 95.12 | 3900 | 0.8059          | 0.1385 |
  | 0.0204        | 97.56 | 4000 | 0.8071          | 0.1389 |
  | 0.0204        | 100.0 | 4100 | 0.8060          | 0.1393 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  