readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_10_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-j-phoneme-colab-3
    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-j-phoneme-colab-3
  
  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_10_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6478
  - Wer: 0.3336
  
  ## 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: 2
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | No log        | 1.0   | 397   | 1.0586          | 0.9425 |
  | No log        | 2.0   | 794   | 0.5773          | 0.5847 |
  | 1.9827        | 3.0   | 1191  | 0.5243          | 0.4882 |
  | 1.9827        | 4.0   | 1588  | 0.4735          | 0.4624 |
  | 1.9827        | 5.0   | 1985  | 0.4967          | 0.4789 |
  | 0.6004        | 6.0   | 2382  | 0.4703          | 0.4246 |
  | 0.6004        | 7.0   | 2779  | 0.4555          | 0.4194 |
  | 0.4911        | 8.0   | 3176  | 0.4692          | 0.4284 |
  | 0.4911        | 9.0   | 3573  | 0.4589          | 0.3997 |
  | 0.4911        | 10.0  | 3970  | 0.4988          | 0.4286 |
  | 0.4275        | 11.0  | 4367  | 0.4851          | 0.4153 |
  | 0.4275        | 12.0  | 4764  | 0.5020          | 0.4039 |
  | 0.3784        | 13.0  | 5161  | 0.5491          | 0.4169 |
  | 0.3784        | 14.0  | 5558  | 0.5211          | 0.4080 |
  | 0.3784        | 15.0  | 5955  | 0.5124          | 0.3950 |
  | 0.3362        | 16.0  | 6352  | 0.5121          | 0.3909 |
  | 0.3362        | 17.0  | 6749  | 0.5503          | 0.3728 |
  | 0.3046        | 18.0  | 7146  | 0.5363          | 0.3915 |
  | 0.3046        | 19.0  | 7543  | 0.6112          | 0.4076 |
  | 0.3046        | 20.0  | 7940  | 0.5884          | 0.3755 |
  | 0.2785        | 21.0  | 8337  | 0.5639          | 0.3793 |
  | 0.2785        | 22.0  | 8734  | 0.6246          | 0.3742 |
  | 0.2513        | 23.0  | 9131  | 0.6014          | 0.3714 |
  | 0.2513        | 24.0  | 9528  | 0.6195          | 0.3697 |
  | 0.2513        | 25.0  | 9925  | 0.6004          | 0.3729 |
  | 0.2296        | 26.0  | 10322 | 0.5793          | 0.3585 |
  | 0.2296        | 27.0  | 10719 | 0.6178          | 0.3628 |
  | 0.2114        | 28.0  | 11116 | 0.5974          | 0.3507 |
  | 0.2114        | 29.0  | 11513 | 0.6056          | 0.3432 |
  | 0.2114        | 30.0  | 11910 | 0.6190          | 0.3536 |
  | 0.1944        | 31.0  | 12307 | 0.6293          | 0.3550 |
  | 0.1944        | 32.0  | 12704 | 0.6236          | 0.3535 |
  | 0.1777        | 33.0  | 13101 | 0.6456          | 0.3503 |
  | 0.1777        | 34.0  | 13498 | 0.6629          | 0.3444 |
  | 0.1777        | 35.0  | 13895 | 0.6585          | 0.3432 |
  | 0.1644        | 36.0  | 14292 | 0.6528          | 0.3455 |
  | 0.1644        | 37.0  | 14689 | 0.6460          | 0.3437 |
  | 0.1521        | 38.0  | 15086 | 0.6441          | 0.3360 |
  | 0.1521        | 39.0  | 15483 | 0.6531          | 0.3350 |
  | 0.1521        | 40.0  | 15880 | 0.6478          | 0.3336 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.10.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  