asr-africa
/

wav2vec2-xls-r-300m-CV-Fleurs-lg-5hrs-v6

@@ -1,199 +1,141 @@
 ---
 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-5hrs-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-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

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