readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: xlsr-wav2vec2-3
    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. -->
  
  # xlsr-wav2vec2-3
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4201
  - Wer: 0.3998
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 800
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 5.0117        | 0.68  | 400   | 3.0284          | 0.9999 |
  | 2.6502        | 1.35  | 800   | 1.0868          | 0.9374 |
  | 0.9362        | 2.03  | 1200  | 0.5216          | 0.6491 |
  | 0.6675        | 2.7   | 1600  | 0.4744          | 0.5837 |
  | 0.5799        | 3.38  | 2000  | 0.4400          | 0.5802 |
  | 0.5196        | 4.05  | 2400  | 0.4266          | 0.5314 |
  | 0.4591        | 4.73  | 2800  | 0.3808          | 0.5190 |
  | 0.4277        | 5.41  | 3200  | 0.3987          | 0.5036 |
  | 0.4125        | 6.08  | 3600  | 0.3902          | 0.5040 |
  | 0.3797        | 6.76  | 4000  | 0.4105          | 0.5025 |
  | 0.3606        | 7.43  | 4400  | 0.3975          | 0.4823 |
  | 0.3554        | 8.11  | 4800  | 0.3733          | 0.4747 |
  | 0.3373        | 8.78  | 5200  | 0.3737          | 0.4726 |
  | 0.3252        | 9.46  | 5600  | 0.3795          | 0.4736 |
  | 0.3192        | 10.14 | 6000  | 0.3935          | 0.4736 |
  | 0.3012        | 10.81 | 6400  | 0.3974          | 0.4648 |
  | 0.2972        | 11.49 | 6800  | 0.4497          | 0.4724 |
  | 0.2873        | 12.16 | 7200  | 0.4645          | 0.4843 |
  | 0.2849        | 12.84 | 7600  | 0.4461          | 0.4709 |
  | 0.274         | 13.51 | 8000  | 0.4002          | 0.4695 |
  | 0.2709        | 14.19 | 8400  | 0.4188          | 0.4627 |
  | 0.2619        | 14.86 | 8800  | 0.3987          | 0.4646 |
  | 0.2545        | 15.54 | 9200  | 0.4083          | 0.4668 |
  | 0.2477        | 16.22 | 9600  | 0.4525          | 0.4728 |
  | 0.2455        | 16.89 | 10000 | 0.4148          | 0.4515 |
  | 0.2281        | 17.57 | 10400 | 0.4304          | 0.4514 |
  | 0.2267        | 18.24 | 10800 | 0.4077          | 0.4446 |
  | 0.2136        | 18.92 | 11200 | 0.4209          | 0.4445 |
  | 0.2032        | 19.59 | 11600 | 0.4543          | 0.4534 |
  | 0.1999        | 20.27 | 12000 | 0.4184          | 0.4373 |
  | 0.1898        | 20.95 | 12400 | 0.4044          | 0.4424 |
  | 0.1846        | 21.62 | 12800 | 0.4098          | 0.4288 |
  | 0.1796        | 22.3  | 13200 | 0.4047          | 0.4262 |
  | 0.1715        | 22.97 | 13600 | 0.4077          | 0.4189 |
  | 0.1641        | 23.65 | 14000 | 0.4162          | 0.4248 |
  | 0.1615        | 24.32 | 14400 | 0.4392          | 0.4222 |
  | 0.1575        | 25.0  | 14800 | 0.4296          | 0.4185 |
  | 0.1456        | 25.68 | 15200 | 0.4363          | 0.4129 |
  | 0.1461        | 26.35 | 15600 | 0.4305          | 0.4124 |
  | 0.1422        | 27.03 | 16000 | 0.4237          | 0.4086 |
  | 0.1378        | 27.7  | 16400 | 0.4294          | 0.4051 |
  | 0.1326        | 28.38 | 16800 | 0.4311          | 0.4051 |
  | 0.1286        | 29.05 | 17200 | 0.4153          | 0.3992 |
  | 0.1283        | 29.73 | 17600 | 0.4201          | 0.3998 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  