--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice model-index: - name: model-facebookptbrlarge results: [] --- # 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 | 0.1730 | | 0.0741 | 17.44 | 24400 | 0.2308 | 0.1674 | | 0.0815 | 17.73 | 24800 | 0.2329 | 0.1655 | | 0.0764 | 18.01 | 25200 | 0.2514 | 0.1711 | | 0.0719 | 18.3 | 25600 | 0.2275 | 0.1578 | | 0.0665 | 18.58 | 26000 | 0.2367 | 0.1614 | | 0.0693 | 18.87 | 26400 | 0.2185 | 0.1593 | | 0.0662 | 19.16 | 26800 | 0.2266 | 0.1678 | | 0.0612 | 19.44 | 27200 | 0.2332 | 0.1602 | | 0.0623 | 19.73 | 27600 | 0.2283 | 0.1670 | | 0.0659 | 20.01 | 28000 | 0.2142 | 0.1626 | | 0.0581 | 20.3 | 28400 | 0.2198 | 0.1646 | | 0.063 | 20.59 | 28800 | 0.2251 | 0.1588 | | 0.0618 | 20.87 | 29200 | 0.2186 | 0.1554 | | 0.0549 | 21.16 | 29600 | 0.2251 | 0.1490 | | 0.058 | 21.44 | 30000 | 0.2366 | 0.1559 | | 0.0543 | 21.73 | 30400 | 0.2262 | 0.1535 | | 0.0529 | 22.02 | 30800 | 0.2358 | 0.1519 | | 0.053 | 22.3 | 31200 | 0.2198 | 0.1513 | | 0.0552 | 22.59 | 31600 | 0.2234 | 0.1503 | | 0.0492 | 22.87 | 32000 | 0.2191 | 0.1516 | | 0.0488 | 23.16 | 32400 | 0.2321 | 0.1500 | | 0.0479 | 23.45 | 32800 | 0.2152 | 0.1420 | | 0.0453 | 23.73 | 33200 | 0.2202 | 0.1453 | | 0.0485 | 24.02 | 33600 | 0.2235 | 0.1468 | | 0.0451 | 24.3 | 34000 | 0.2192 | 0.1455 | | 0.041 | 24.59 | 34400 | 0.2138 | 0.1438 | | 0.0435 | 24.87 | 34800 | 0.2335 | 0.1423 | | 0.0404 | 25.16 | 35200 | 0.2220 | 0.1409 | | 0.0374 | 25.45 | 35600 | 0.2366 | 0.1437 | | 0.0405 | 25.73 | 36000 | 0.2233 | 0.1428 | | 0.0385 | 26.02 | 36400 | 0.2208 | 0.1414 | | 0.0373 | 26.3 | 36800 | 0.2265 | 0.1420 | | 0.0365 | 26.59 | 37200 | 0.2174 | 0.1402 | | 0.037 | 26.88 | 37600 | 0.2249 | 0.1397 | | 0.0379 | 27.16 | 38000 | 0.2173 | 0.1374 | | 0.0354 | 27.45 | 38400 | 0.2212 | 0.1381 | | 0.034 | 27.73 | 38800 | 0.2313 | 0.1364 | | 0.0347 | 28.02 | 39200 | 0.2230 | 0.1356 | | 0.0318 | 28.31 | 39600 | 0.2231 | 0.1357 | | 0.0305 | 28.59 | 40000 | 0.2281 | 0.1366 | | 0.0307 | 28.88 | 40400 | 0.2259 | 0.1342 | | 0.0315 | 29.16 | 40800 | 0.2252 | 0.1332 | | 0.0314 | 29.45 | 41200 | 0.2218 | 0.1328 | | 0.0307 | 29.74 | 41600 | 0.2206 | 0.1322 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.8.1+cu111 - Datasets 2.2.1 - Tokenizers 0.12.1