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-new
    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-new
  
  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: 0.5498
  - Wer: 0.3257
  
  ## 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: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 397  | 0.7976          | 0.7045 |
  | No log        | 2.0   | 794  | 0.5777          | 0.5723 |
  | 1.7064        | 3.0   | 1191 | 0.4775          | 0.4706 |
  | 1.7064        | 4.0   | 1588 | 0.4755          | 0.4580 |
  | 1.7064        | 5.0   | 1985 | 0.4678          | 0.4250 |
  | 0.3823        | 6.0   | 2382 | 0.4742          | 0.4196 |
  | 0.3823        | 7.0   | 2779 | 0.4419          | 0.3817 |
  | 0.2485        | 8.0   | 3176 | 0.4402          | 0.3711 |
  | 0.2485        | 9.0   | 3573 | 0.4942          | 0.3703 |
  | 0.2485        | 10.0  | 3970 | 0.4877          | 0.3613 |
  | 0.1735        | 11.0  | 4367 | 0.5073          | 0.3453 |
  | 0.1735        | 12.0  | 4764 | 0.5127          | 0.3354 |
  | 0.1238        | 13.0  | 5161 | 0.5545          | 0.3392 |
  | 0.1238        | 14.0  | 5558 | 0.5419          | 0.3290 |
  | 0.1238        | 15.0  | 5955 | 0.5498          | 0.3257 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.10.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  