--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-xls-r-300m tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-xls-r-300m-CV-Fleurs-lg-5hrs-v6 results: [] --- # wav2vec2-xls-r-300m-CV-Fleurs-lg-5hrs-v6 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3699 - Wer: 0.7068 - Cer: 0.1674 ## 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: 4 - eval_batch_size: 2 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| | 3.4673 | 1.0 | 515 | 2.9455 | 1.0 | 1.0 | | 2.7771 | 2.0 | 1030 | 2.2858 | 1.0 | 0.8202 | | 1.8563 | 3.0 | 1545 | 1.3887 | 0.9943 | 0.3860 | | 1.4104 | 4.0 | 2060 | 1.1308 | 0.9612 | 0.3178 | | 1.2231 | 5.0 | 2575 | 1.0093 | 0.9368 | 0.2874 | | 1.0872 | 6.0 | 3090 | 0.9377 | 0.9282 | 0.2764 | | 0.9686 | 7.0 | 3605 | 0.8713 | 0.9118 | 0.2548 | | 0.8675 | 8.0 | 4120 | 0.8353 | 0.9062 | 0.2504 | | 0.7817 | 9.0 | 4635 | 0.8204 | 0.8985 | 0.2440 | | 0.7045 | 10.0 | 5150 | 0.8144 | 0.8841 | 0.2332 | | 0.6322 | 11.0 | 5665 | 0.8112 | 0.8416 | 0.2176 | | 0.5865 | 12.0 | 6180 | 0.8228 | 0.8404 | 0.2203 | | 0.5264 | 13.0 | 6695 | 0.8488 | 0.8297 | 0.2149 | | 0.4879 | 14.0 | 7210 | 0.8404 | 0.8047 | 0.2070 | | 0.4408 | 15.0 | 7725 | 0.9070 | 0.8233 | 0.2115 | | 0.4079 | 16.0 | 8240 | 0.9762 | 0.8107 | 0.2087 | | 0.3777 | 17.0 | 8755 | 0.8993 | 0.8119 | 0.2063 | | 0.356 | 18.0 | 9270 | 1.0907 | 0.8091 | 0.2071 | | 0.3234 | 19.0 | 9785 | 1.0084 | 0.8201 | 0.2042 | | 0.3157 | 20.0 | 10300 | 0.9811 | 0.8201 | 0.2032 | | 0.2892 | 21.0 | 10815 | 1.0994 | 0.8067 | 0.1999 | | 0.2793 | 22.0 | 11330 | 1.0639 | 0.7842 | 0.1986 | | 0.2609 | 23.0 | 11845 | 1.0425 | 0.7925 | 0.1996 | | 0.2535 | 24.0 | 12360 | 1.0799 | 0.7888 | 0.1988 | | 0.2422 | 25.0 | 12875 | 1.0773 | 0.7795 | 0.1932 | | 0.2336 | 26.0 | 13390 | 1.0731 | 0.7732 | 0.1930 | | 0.2241 | 27.0 | 13905 | 1.1465 | 0.7730 | 0.1907 | | 0.205 | 28.0 | 14420 | 1.1303 | 0.7853 | 0.1935 | | 0.2045 | 29.0 | 14935 | 1.1377 | 0.7825 | 0.1919 | | 0.2004 | 30.0 | 15450 | 1.1406 | 0.7701 | 0.1884 | | 0.1874 | 31.0 | 15965 | 1.2273 | 0.7749 | 0.1869 | | 0.1901 | 32.0 | 16480 | 1.2571 | 0.7551 | 0.1846 | | 0.178 | 33.0 | 16995 | 1.2050 | 0.7666 | 0.1900 | | 0.176 | 34.0 | 17510 | 1.2171 | 0.7550 | 0.1842 | | 0.174 | 35.0 | 18025 | 1.2065 | 0.7790 | 0.1850 | | 0.1668 | 36.0 | 18540 | 1.2275 | 0.7582 | 0.1863 | | 0.1663 | 37.0 | 19055 | 1.2588 | 0.7574 | 0.1862 | | 0.1673 | 38.0 | 19570 | 1.2510 | 0.7556 | 0.1830 | | 0.1542 | 39.0 | 20085 | 1.2482 | 0.7526 | 0.1818 | | 0.1504 | 40.0 | 20600 | 1.2521 | 0.7545 | 0.1831 | | 0.1524 | 41.0 | 21115 | 1.3708 | 0.7838 | 0.1863 | | 0.1425 | 42.0 | 21630 | 1.2846 | 0.7711 | 0.1838 | | 0.1458 | 43.0 | 22145 | 1.2877 | 0.7509 | 0.1820 | | 0.1416 | 44.0 | 22660 | 1.2903 | 0.7581 | 0.1810 | | 0.137 | 45.0 | 23175 | 1.2775 | 0.7472 | 0.1807 | | 0.131 | 46.0 | 23690 | 1.3168 | 0.7404 | 0.1793 | | 0.1384 | 47.0 | 24205 | 1.2914 | 0.7545 | 0.1805 | | 0.1281 | 48.0 | 24720 | 1.2716 | 0.7421 | 0.1799 | | 0.1306 | 49.0 | 25235 | 1.3053 | 0.7443 | 0.1784 | | 0.1326 | 50.0 | 25750 | 1.3336 | 0.7419 | 0.1795 | | 0.1202 | 51.0 | 26265 | 1.3539 | 0.7342 | 0.1784 | | 0.1182 | 52.0 | 26780 | 1.3186 | 0.7584 | 0.1812 | | 0.117 | 53.0 | 27295 | 1.3012 | 0.7317 | 0.1757 | | 0.1154 | 54.0 | 27810 | 1.2908 | 0.7333 | 0.1757 | | 0.1123 | 55.0 | 28325 | 1.3116 | 0.7356 | 0.1762 | | 0.1124 | 56.0 | 28840 | 1.3920 | 0.7315 | 0.1745 | | 0.1185 | 57.0 | 29355 | 1.3557 | 0.7285 | 0.1737 | | 0.1032 | 58.0 | 29870 | 1.3676 | 0.7260 | 0.1742 | | 0.1047 | 59.0 | 30385 | 1.3938 | 0.7328 | 0.1743 | | 0.1047 | 60.0 | 30900 | 1.3472 | 0.7355 | 0.1761 | | 0.1047 | 61.0 | 31415 | 1.3843 | 0.7294 | 0.1739 | | 0.1008 | 62.0 | 31930 | 1.3270 | 0.7314 | 0.1749 | | 0.0971 | 63.0 | 32445 | 1.3778 | 0.7297 | 0.1739 | | 0.0947 | 64.0 | 32960 | 1.3629 | 0.7253 | 0.1734 | | 0.0955 | 65.0 | 33475 | 1.4170 | 0.7174 | 0.1716 | | 0.0977 | 66.0 | 33990 | 1.3668 | 0.7118 | 0.1707 | | 0.0961 | 67.0 | 34505 | 1.4107 | 0.7150 | 0.1709 | | 0.093 | 68.0 | 35020 | 1.4030 | 0.7140 | 0.1701 | | 0.0856 | 69.0 | 35535 | 1.3854 | 0.7068 | 0.1681 | | 0.0879 | 70.0 | 36050 | 1.3952 | 0.7152 | 0.1706 | | 0.0878 | 71.0 | 36565 | 1.4117 | 0.7219 | 0.1717 | | 0.0842 | 72.0 | 37080 | 1.4185 | 0.7131 | 0.1699 | | 0.0833 | 73.0 | 37595 | 1.3656 | 0.7099 | 0.1684 | | 0.081 | 74.0 | 38110 | 1.3637 | 0.7091 | 0.1694 | | 0.0798 | 75.0 | 38625 | 1.4499 | 0.7156 | 0.1701 | | 0.0783 | 76.0 | 39140 | 1.4385 | 0.7126 | 0.1700 | | 0.0767 | 77.0 | 39655 | 1.4507 | 0.7058 | 0.1674 | | 0.0772 | 78.0 | 40170 | 1.4279 | 0.7058 | 0.1683 | | 0.0785 | 79.0 | 40685 | 1.3699 | 0.7068 | 0.1674 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.1.0+cu118 - Datasets 3.1.0 - Tokenizers 0.20.1