readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: victor-hg-ptbr-2.0
    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. -->
  
  # victor-hg-ptbr-2.0
  
  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: 0.0240
  - Wer: 0.0219
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 4.4069        | 0.21  | 400   | 1.1372          | 0.9140 |
  | 0.8079        | 0.43  | 800   | 0.5822          | 0.5339 |
  | 0.5821        | 0.64  | 1200  | 0.4226          | 0.4177 |
  | 0.5159        | 0.86  | 1600  | 0.4074          | 0.3970 |
  | 0.4484        | 1.07  | 2000  | 0.3144          | 0.3220 |
  | 0.3937        | 1.29  | 2400  | 0.3160          | 0.3264 |
  | 0.3911        | 1.5   | 2800  | 0.2863          | 0.2956 |
  | 0.3761        | 1.71  | 3200  | 0.3029          | 0.3128 |
  | 0.3722        | 1.93  | 3600  | 0.2771          | 0.2933 |
  | 0.3193        | 2.14  | 4000  | 0.2603          | 0.2795 |
  | 0.3013        | 2.36  | 4400  | 0.2682          | 0.2703 |
  | 0.3039        | 2.57  | 4800  | 0.2630          | 0.2618 |
  | 0.3133        | 2.79  | 5200  | 0.2578          | 0.2629 |
  | 0.3173        | 3.0   | 5600  | 0.2640          | 0.2746 |
  | 0.2521        | 3.22  | 6000  | 0.2797          | 0.2662 |
  | 0.2654        | 3.43  | 6400  | 0.2762          | 0.2640 |
  | 0.2586        | 3.64  | 6800  | 0.2642          | 0.2596 |
  | 0.265         | 3.86  | 7200  | 0.2656          | 0.2794 |
  | 0.2432        | 4.07  | 7600  | 0.2459          | 0.2497 |
  | 0.226         | 4.29  | 8000  | 0.2533          | 0.2509 |
  | 0.2385        | 4.5   | 8400  | 0.2332          | 0.2394 |
  | 0.2332        | 4.72  | 8800  | 0.2500          | 0.2569 |
  | 0.2358        | 4.93  | 9200  | 0.2384          | 0.2489 |
  | 0.2169        | 5.14  | 9600  | 0.2410          | 0.2380 |
  | 0.2038        | 5.36  | 10000 | 0.2426          | 0.2333 |
  | 0.2109        | 5.57  | 10400 | 0.2480          | 0.2473 |
  | 0.2147        | 5.79  | 10800 | 0.2341          | 0.2272 |
  | 0.2153        | 6.0   | 11200 | 0.2402          | 0.2424 |
  | 0.186         | 6.22  | 11600 | 0.2560          | 0.2489 |
  | 0.1854        | 6.43  | 12000 | 0.2444          | 0.2402 |
  | 0.1915        | 6.65  | 12400 | 0.2720          | 0.2531 |
  | 0.1929        | 6.86  | 12800 | 0.2516          | 0.2342 |
  | 0.1842        | 7.07  | 13200 | 0.2480          | 0.2304 |
  | 0.1682        | 7.29  | 13600 | 0.2393          | 0.2276 |
  | 0.1753        | 7.5   | 14000 | 0.2514          | 0.2263 |
  | 0.1798        | 7.72  | 14400 | 0.2191          | 0.2178 |
  | 0.1736        | 7.93  | 14800 | 0.2351          | 0.2197 |
  | 0.1668        | 8.15  | 15200 | 0.2315          | 0.2194 |
  | 0.1545        | 8.36  | 15600 | 0.2291          | 0.2079 |
  | 0.1508        | 8.57  | 16000 | 0.2351          | 0.2134 |
  | 0.1662        | 8.79  | 16400 | 0.2298          | 0.2197 |
  | 0.1621        | 9.0   | 16800 | 0.2314          | 0.2219 |
  | 0.1416        | 9.22  | 17200 | 0.2306          | 0.2192 |
  | 0.1455        | 9.43  | 17600 | 0.2466          | 0.2184 |
  | 0.1522        | 9.65  | 18000 | 0.2392          | 0.2255 |
  | 0.1434        | 9.86  | 18400 | 0.2464          | 0.2208 |
  | 0.1362        | 10.08 | 18800 | 0.2351          | 0.2095 |
  | 0.127         | 10.29 | 19200 | 0.2373          | 0.2110 |
  | 0.133         | 10.5  | 19600 | 0.2269          | 0.2031 |
  | 0.1308        | 10.72 | 20000 | 0.2400          | 0.2096 |
  | 0.1331        | 10.93 | 20400 | 0.2243          | 0.2083 |
  | 0.125         | 11.15 | 20800 | 0.2334          | 0.2063 |
  | 0.1236        | 11.36 | 21200 | 0.2195          | 0.2044 |
  | 0.1263        | 11.58 | 21600 | 0.2263          | 0.2050 |
  | 0.1235        | 11.79 | 22000 | 0.2217          | 0.2087 |
  | 0.1301        | 12.0  | 22400 | 0.2332          | 0.2094 |
  | 0.1123        | 12.22 | 22800 | 0.2195          | 0.2068 |
  | 0.117         | 12.43 | 23200 | 0.2266          | 0.2110 |
  | 0.1156        | 12.65 | 23600 | 0.2469          | 0.2063 |
  | 0.1117        | 12.86 | 24000 | 0.2379          | 0.2035 |
  | 0.1124        | 13