asr-africa
/

wav2vec2-xls-r-300m-CV-Fleurs-lg-10hrs-v6

@@ -1,199 +1,162 @@
 ---
 library_name: transformers
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 ---
 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-10hrs-v6
+  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. -->
+# wav2vec2-xls-r-300m-CV-Fleurs-lg-10hrs-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: 1.3042
+- Wer: 0.6058
+- Cer: 0.1381
+## 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    |
+|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
+| 3.1664        | 1.0   | 1025   | 2.5342          | 1.0    | 0.8840 |
+| 1.8493        | 2.0   | 2050   | 1.2129          | 0.9929 | 0.3862 |
+| 1.2976        | 3.0   | 3075   | 0.9944          | 0.9482 | 0.2930 |
+| 1.1249        | 4.0   | 4100   | 0.9405          | 0.9249 | 0.2753 |
+| 0.9905        | 5.0   | 5125   | 0.8406          | 0.9072 | 0.2535 |
+| 0.8961        | 6.0   | 6150   | 0.8121          | 0.8699 | 0.2368 |
+| 0.8101        | 7.0   | 7175   | 0.7705          | 0.8607 | 0.2273 |
+| 0.728         | 8.0   | 8200   | 0.7325          | 0.8330 | 0.2163 |
+| 0.6653        | 9.0   | 9225   | 0.7483          | 0.8089 | 0.2060 |
+| 0.6063        | 10.0  | 10250  | 0.7343          | 0.7981 | 0.2018 |
+| 0.5503        | 11.0  | 11275  | 0.7499          | 0.7667 | 0.1887 |
+| 0.5016        | 12.0  | 12300  | 0.7474          | 0.7734 | 0.1917 |
+| 0.4574        | 13.0  | 13325  | 0.7665          | 0.7479 | 0.1858 |
+| 0.4227        | 14.0  | 14350  | 0.8014          | 0.7605 | 0.1866 |
+| 0.3898        | 15.0  | 15375  | 0.8140          | 0.7618 | 0.1817 |
+| 0.3664        | 16.0  | 16400  | 0.7794          | 0.7234 | 0.1758 |
+| 0.3389        | 17.0  | 17425  | 0.8175          | 0.7290 | 0.1762 |
+| 0.3155        | 18.0  | 18450  | 0.8647          | 0.7284 | 0.1799 |
+| 0.2991        | 19.0  | 19475  | 0.8268          | 0.7134 | 0.1731 |
+| 0.2825        | 20.0  | 20500  | 0.9408          | 0.7312 | 0.1756 |
+| 0.2665        | 21.0  | 21525  | 0.9131          | 0.7307 | 0.1715 |
+| 0.253         | 22.0  | 22550  | 0.9645          | 0.7242 | 0.1747 |
+| 0.2354        | 23.0  | 23575  | 0.9436          | 0.7125 | 0.1699 |
+| 0.231         | 24.0  | 24600  | 0.9521          | 0.7239 | 0.1702 |
+| 0.2178        | 25.0  | 25625  | 0.9751          | 0.7076 | 0.1694 |
+| 0.2086        | 26.0  | 26650  | 0.9704          | 0.6945 | 0.1689 |
+| 0.2002        | 27.0  | 27675  | 0.9937          | 0.7077 | 0.1682 |
+| 0.1968        | 28.0  | 28700  | 0.9523          | 0.6959 | 0.1682 |
+| 0.1889        | 29.0  | 29725  | 1.0351          | 0.6908 | 0.1653 |
+| 0.182         | 30.0  | 30750  | 1.0054          | 0.6933 | 0.1644 |
+| 0.1723        | 31.0  | 31775  | 1.0039          | 0.6930 | 0.1646 |
+| 0.1695        | 32.0  | 32800  | 1.0005          | 0.6855 | 0.1632 |
+| 0.1633        | 33.0  | 33825  | 1.0273          | 0.6897 | 0.1633 |
+| 0.1571        | 34.0  | 34850  | 1.0361          | 0.6850 | 0.1615 |
+| 0.1573        | 35.0  | 35875  | 1.0092          | 0.6767 | 0.1604 |
+| 0.1511        | 36.0  | 36900  | 1.0353          | 0.6816 | 0.1622 |
+| 0.1469        | 37.0  | 37925  | 1.0394          | 0.6716 | 0.1618 |
+| 0.1495        | 38.0  | 38950  | 1.1006          | 0.6804 | 0.1621 |
+| 0.1411        | 39.0  | 39975  | 1.1300          | 0.6742 | 0.1603 |
+| 0.1391        | 40.0  | 41000  | 1.0378          | 0.6801 | 0.1591 |
+| 0.138         | 41.0  | 42025  | 1.0655          | 0.6679 | 0.1581 |
+| 0.1304        | 42.0  | 43050  | 1.1279          | 0.6777 | 0.1594 |
+| 0.1308        | 43.0  | 44075  | 1.0743          | 0.6786 | 0.1572 |
+| 0.128         | 44.0  | 45100  | 1.1424          | 0.6683 | 0.1569 |
+| 0.1261        | 45.0  | 46125  | 1.0351          | 0.6787 | 0.1596 |
+| 0.1242        | 46.0  | 47150  | 1.1587          | 0.6656 | 0.1556 |
+| 0.1179        | 47.0  | 48175  | 1.1617          | 0.6538 | 0.1555 |
+| 0.1164        | 48.0  | 49200  | 1.1593          | 0.6604 | 0.1567 |
+| 0.1137        | 49.0  | 50225  | 1.1450          | 0.6622 | 0.1554 |
+| 0.1102        | 50.0  | 51250  | 1.1221          | 0.6593 | 0.1555 |
+| 0.1107        | 51.0  | 52275  | 1.1194          | 0.6618 | 0.1538 |
+| 0.1088        | 52.0  | 53300  | 1.1452          | 0.6503 | 0.1527 |
+| 0.1078        | 53.0  | 54325  | 1.1679          | 0.6529 | 0.1529 |
+| 0.1054        | 54.0  | 55350  | 1.1926          | 0.6437 | 0.1503 |
+| 0.1012        | 55.0  | 56375  | 1.1483          | 0.6568 | 0.1531 |
+| 0.1047        | 56.0  | 57400  | 1.1756          | 0.6544 | 0.1528 |
+| 0.0958        | 57.0  | 58425  | 1.2168          | 0.6531 | 0.1512 |
+| 0.0966        | 58.0  | 59450  | 1.1973          | 0.6383 | 0.1493 |
+| 0.0966        | 59.0  | 60475  | 1.1830          | 0.6493 | 0.1511 |
+| 0.0948        | 60.0  | 61500  | 1.2027          | 0.6438 | 0.1509 |
+| 0.0888        | 61.0  | 62525  | 1.1959          | 0.6413 | 0.1498 |
+| 0.0909        | 62.0  | 63550  | 1.2046          | 0.6507 | 0.1512 |
+| 0.0888        | 63.0  | 64575  | 1.2052          | 0.6347 | 0.1487 |
+| 0.0869        | 64.0  | 65600  | 1.2118          | 0.6324 | 0.1482 |
+| 0.0846        | 65.0  | 66625  | 1.1967          | 0.6365 | 0.1480 |
+| 0.0833        | 66.0  | 67650  | 1.1957          | 0.6323 | 0.1460 |
+| 0.0827        | 67.0  | 68675  | 1.1928          | 0.6370 | 0.1470 |
+| 0.0824        | 68.0  | 69700  | 1.2578          | 0.6416 | 0.1472 |
+| 0.08          | 69.0  | 70725  | 1.2427          | 0.6284 | 0.1447 |
+| 0.0787        | 70.0  | 71750  | 1.2061          | 0.6295 | 0.1462 |
+| 0.0777        | 71.0  | 72775  | 1.2185          | 0.6315 | 0.1454 |
+| 0.0736        | 72.0  | 73800  | 1.2454          | 0.6237 | 0.1445 |
+| 0.0746        | 73.0  | 74825  | 1.2629          | 0.6298 | 0.1464 |
+| 0.0735        | 74.0  | 75850  | 1.2398          | 0.6218 | 0.1428 |
+| 0.0724        | 75.0  | 76875  | 1.2727          | 0.6269 | 0.1440 |
+| 0.0698        | 76.0  | 77900  | 1.2327          | 0.6259 | 0.1439 |
+| 0.0677        | 77.0  | 78925  | 1.2338          | 0.6213 | 0.1442 |
+| 0.0699        | 78.0  | 79950  | 1.2755          | 0.6226 | 0.1442 |
+| 0.0656        | 79.0  | 80975  | 1.2734          | 0.6237 | 0.1431 |
+| 0.0622        | 80.0  | 82000  | 1.2733          | 0.6211 | 0.1427 |
+| 0.0648        | 81.0  | 83025  | 1.2345          | 0.6274 | 0.1421 |
+| 0.0626        | 82.0  | 84050  | 1.2670          | 0.6273 | 0.1430 |
+| 0.0632        | 83.0  | 85075  | 1.2634          | 0.6150 | 0.1422 |
+| 0.0611        | 84.0  | 86100  | 1.3266          | 0.6192 | 0.1418 |
+| 0.0608        | 85.0  | 87125  | 1.2889          | 0.6153 | 0.1414 |
+| 0.0581        | 86.0  | 88150  | 1.2808          | 0.6146 | 0.1406 |
+| 0.0586        | 87.0  | 89175  | 1.3120          | 0.6142 | 0.1406 |
+| 0.0575        | 88.0  | 90200  | 1.2701          | 0.6171 | 0.1409 |
+| 0.0577        | 89.0  | 91225  | 1.2916          | 0.6116 | 0.1400 |
+| 0.0569        | 90.0  | 92250  | 1.3074          | 0.6132 | 0.1401 |
+| 0.0552        | 91.0  | 93275  | 1.3030          | 0.6115 | 0.1388 |
+| 0.0563        | 92.0  | 94300  | 1.2719          | 0.6082 | 0.1387 |
+| 0.0516        | 93.0  | 95325  | 1.2853          | 0.6078 | 0.1380 |
+| 0.0523        | 94.0  | 96350  | 1.2953          | 0.6096 | 0.1389 |
+| 0.0489        | 95.0  | 97375  | 1.3099          | 0.6097 | 0.1387 |
+| 0.0513        | 96.0  | 98400  | 1.3082          | 0.6095 | 0.1388 |
+| 0.0522        | 97.0  | 99425  | 1.3076          | 0.6097 | 0.1384 |
+| 0.0498        | 98.0  | 100450 | 1.3003          | 0.6073 | 0.1383 |
+| 0.0506        | 99.0  | 101475 | 1.3012          | 0.6067 | 0.1382 |
+| 0.0491        | 100.0 | 102500 | 1.3042          | 0.6058 | 0.1381 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.1.0+cu118
+- Datasets 3.1.0
+- Tokenizers 0.20.1