readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: model-facebookptbrlarge
    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. -->
  
  # model-facebookptbrlarge
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53-portuguese](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-portuguese) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2206
  - Wer: 0.1322
  
  ## 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: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 5.8975        | 0.29  | 400   | 0.4131          | 0.3336 |
  | 0.5131        | 0.57  | 800   | 0.4103          | 0.3293 |
  | 0.4846        | 0.86  | 1200  | 0.3493          | 0.3028 |
  | 0.4174        | 1.14  | 1600  | 0.3055          | 0.2730 |
  | 0.4105        | 1.43  | 2000  | 0.3283          | 0.3041 |
  | 0.4028        | 1.72  | 2400  | 0.3539          | 0.3210 |
  | 0.386         | 2.0   | 2800  | 0.2925          | 0.2690 |
  | 0.3224        | 2.29  | 3200  | 0.2842          | 0.2665 |
  | 0.3122        | 2.57  | 3600  | 0.2781          | 0.2472 |
  | 0.3087        | 2.86  | 4000  | 0.2794          | 0.2692 |
  | 0.2878        | 3.15  | 4400  | 0.2795          | 0.2537 |
  | 0.2915        | 3.43  | 4800  | 0.2764          | 0.2478 |
  | 0.2816        | 3.72  | 5200  | 0.2761          | 0.2366 |
  | 0.283         | 4.0   | 5600  | 0.2641          | 0.2587 |
  | 0.2448        | 4.29  | 6000  | 0.2489          | 0.2417 |
  | 0.247         | 4.57  | 6400  | 0.2538          | 0.2422 |
  | 0.25          | 4.86  | 6800  | 0.2660          | 0.2306 |
  | 0.2256        | 5.15  | 7200  | 0.2477          | 0.2267 |
  | 0.2225        | 5.43  | 7600  | 0.2364          | 0.2195 |
  | 0.2217        | 5.72  | 8000  | 0.2319          | 0.2139 |
  | 0.2272        | 6.0   | 8400  | 0.2489          | 0.2427 |
  | 0.2016        | 6.29  | 8800  | 0.2404          | 0.2181 |
  | 0.1973        | 6.58  | 9200  | 0.2532          | 0.2273 |
  | 0.2101        | 6.86  | 9600  | 0.2590          | 0.2100 |
  | 0.1946        | 7.15  | 10000 | 0.2414          | 0.2108 |
  | 0.1845        | 7.43  | 10400 | 0.2485          | 0.2124 |
  | 0.1861        | 7.72  | 10800 | 0.2405          | 0.2124 |
  | 0.1851        | 8.01  | 11200 | 0.2449          | 0.2062 |
  | 0.1587        | 8.29  | 11600 | 0.2510          | 0.2048 |
  | 0.1694        | 8.58  | 12000 | 0.2290          | 0.2059 |
  | 0.1637        | 8.86  | 12400 | 0.2376          | 0.2063 |
  | 0.1594        | 9.15  | 12800 | 0.2307          | 0.1967 |
  | 0.1537        | 9.44  | 13200 | 0.2274          | 0.2017 |
  | 0.1498        | 9.72  | 13600 | 0.2322          | 0.2025 |
  | 0.1516        | 10.01 | 14000 | 0.2323          | 0.1971 |
  | 0.1336        | 10.29 | 14400 | 0.2249          | 0.1920 |
  | 0.134         | 10.58 | 14800 | 0.2258          | 0.2055 |
  | 0.138         | 10.86 | 15200 | 0.2250          | 0.1906 |
  | 0.13          | 11.15 | 15600 | 0.2423          | 0.1920 |
  | 0.1302        | 11.44 | 16000 | 0.2294          | 0.1849 |
  | 0.1253        | 11.72 | 16400 | 0.2193          | 0.1889 |
  | 0.1219        | 12.01 | 16800 | 0.2350          | 0.1869 |
  | 0.1149        | 12.29 | 17200 | 0.2350          | 0.1903 |
  | 0.1161        | 12.58 | 17600 | 0.2277          | 0.1899 |
  | 0.1129        | 12.87 | 18000 | 0.2416          | 0.1855 |
  | 0.1091        | 13.15 | 18400 | 0.2289          | 0.1815 |
  | 0.1073        | 13.44 | 18800 | 0.2383          | 0.1799 |
  | 0.1135        | 13.72 | 19200 | 0.2306          | 0.1819 |
  | 0.1075        | 14.01 | 19600 | 0.2283          | 0.1742 |
  | 0.0971        | 14.3  | 20000 | 0.2271          | 0.1851 |
  | 0.0967        | 14.58 | 20400 | 0.2395          | 0.1809 |
  | 0.1039        | 14.87 | 20800 | 0.2286          | 0.1808 |
  | 0.0984        | 15.15 | 21200 | 0.2303          | 0.1821 |
  | 0.0922        | 15.44 | 21600 | 0.2254          | 0.1745 |
  | 0.0882        | 15.73 | 22000 | 0.2280          | 0.1836 |
  | 0.0859        | 16.01 | 22400 | 0.2355          | 0.1779 |
  | 0.0832        | 16.3  | 22800 | 0.2347          | 0.1740 |
  | 0.0854        | 16.58 | 23200 | 0.2342          | 0.1739 |
  | 0.0874        | 16.87 | 23600 | 0.2316          | 0.1719 |
  | 0.0808        | 17.16 | 24000 | 0.2291   