asr-africa
/

wav2vec2-xls-r-300m-CV_Fleurs_AMMI_ALFFA-sw-10hrs-v1

@@ -1,199 +1,164 @@
 ---
 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_AMMI_ALFFA-sw-10hrs-v1
+  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_AMMI_ALFFA-sw-10hrs-v1
+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: 1.2971
+- Wer: 0.3556
+- Cer: 0.1044
+## 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: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- 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    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
+| 7.0482        | 0.9986  | 360   | 2.9509          | 1.0    | 1.0    |
+| 5.5647        | 2.0     | 721   | 2.1843          | 1.0    | 0.6661 |
+| 3.4187        | 2.9986  | 1081  | 1.3719          | 0.9273 | 0.3550 |
+| 2.5943        | 4.0     | 1442  | 1.1633          | 0.8977 | 0.2827 |
+| 2.1874        | 4.9986  | 1802  | 0.9978          | 0.7963 | 0.2396 |
+| 1.8944        | 6.0     | 2163  | 0.8786          | 0.7200 | 0.2105 |
+| 1.6523        | 6.9986  | 2523  | 0.8251          | 0.6626 | 0.1915 |
+| 1.4683        | 8.0     | 2884  | 0.7958          | 0.6460 | 0.1890 |
+| 1.3358        | 8.9986  | 3244  | 0.7706          | 0.6021 | 0.1754 |
+| 1.1904        | 10.0    | 3605  | 0.7385          | 0.5992 | 0.1751 |
+| 1.0935        | 10.9986 | 3965  | 0.7722          | 0.5620 | 0.1655 |
+| 1.0084        | 12.0    | 4326  | 0.7509          | 0.5715 | 0.1697 |
+| 0.9096        | 12.9986 | 4686  | 0.7622          | 0.5253 | 0.1503 |
+| 0.8377        | 14.0    | 5047  | 0.7561          | 0.5150 | 0.1496 |
+| 0.7773        | 14.9986 | 5407  | 0.7909          | 0.5108 | 0.1511 |
+| 0.7337        | 16.0    | 5768  | 0.7987          | 0.5079 | 0.1481 |
+| 0.6904        | 16.9986 | 6128  | 0.8391          | 0.4989 | 0.1426 |
+| 0.6381        | 18.0    | 6489  | 0.8506          | 0.5009 | 0.1422 |
+| 0.6163        | 18.9986 | 6849  | 0.8754          | 0.4815 | 0.1392 |
+| 0.5792        | 20.0    | 7210  | 0.9556          | 0.4788 | 0.1373 |
+| 0.5665        | 20.9986 | 7570  | 0.8177          | 0.4739 | 0.1371 |
+| 0.5387        | 22.0    | 7931  | 0.8381          | 0.4704 | 0.1375 |
+| 0.5125        | 22.9986 | 8291  | 0.8817          | 0.4589 | 0.1323 |
+| 0.4893        | 24.0    | 8652  | 0.9227          | 0.4590 | 0.1344 |
+| 0.4702        | 24.9986 | 9012  | 1.0008          | 0.4470 | 0.1294 |
+| 0.4583        | 26.0    | 9373  | 0.9699          | 0.4488 | 0.1298 |
+| 0.448         | 26.9986 | 9733  | 1.0021          | 0.4525 | 0.1320 |
+| 0.4358        | 28.0    | 10094 | 0.9996          | 0.4459 | 0.1313 |
+| 0.42          | 28.9986 | 10454 | 0.9673          | 0.4434 | 0.1273 |
+| 0.3913        | 30.0    | 10815 | 1.0123          | 0.4410 | 0.1272 |
+| 0.4023        | 30.9986 | 11175 | 1.0258          | 0.4308 | 0.1258 |
+| 0.3793        | 32.0    | 11536 | 1.0015          | 0.4334 | 0.1269 |
+| 0.3716        | 32.9986 | 11896 | 1.0227          | 0.4370 | 0.1273 |
+| 0.3668        | 34.0    | 12257 | 1.0355          | 0.4283 | 0.1251 |
+| 0.3442        | 34.9986 | 12617 | 1.0020          | 0.4264 | 0.1235 |
+| 0.3392        | 36.0    | 12978 | 1.0422          | 0.4214 | 0.1238 |
+| 0.3229        | 36.9986 | 13338 | 1.0545          | 0.4219 | 0.1236 |
+| 0.311         | 38.0    | 13699 | 1.0842          | 0.4227 | 0.1242 |
+| 0.3046        | 38.9986 | 14059 | 1.0755          | 0.4168 | 0.1208 |
+| 0.2966        | 40.0    | 14420 | 1.0766          | 0.4206 | 0.1239 |
+| 0.289         | 40.9986 | 14780 | 1.0696          | 0.4119 | 0.1209 |
+| 0.2801        | 42.0    | 15141 | 1.0653          | 0.4127 | 0.1215 |
+| 0.2845        | 42.9986 | 15501 | 1.1241          | 0.4138 | 0.1215 |
+| 0.2795        | 44.0    | 15862 | 1.1176          | 0.4077 | 0.1195 |
+| 0.2742        | 44.9986 | 16222 | 1.0823          | 0.4092 | 0.1198 |
+| 0.2772        | 46.0    | 16583 | 1.0684          | 0.4111 | 0.1214 |
+| 0.2607        | 46.9986 | 16943 | 1.1543          | 0.4055 | 0.1191 |
+| 0.2565        | 48.0    | 17304 | 1.1207          | 0.4042 | 0.1186 |
+| 0.2397        | 48.9986 | 17664 | 1.1324          | 0.4023 | 0.1184 |
+| 0.2439        | 50.0    | 18025 | 1.0794          | 0.4058 | 0.1192 |
+| 0.2393        | 50.9986 | 18385 | 1.1105          | 0.4002 | 0.1177 |
+| 0.2283        | 52.0    | 18746 | 1.1724          | 0.3938 | 0.1162 |
+| 0.226         | 52.9986 | 19106 | 1.1660          | 0.3975 | 0.1175 |
+| 0.2272        | 54.0    | 19467 | 1.1530          | 0.3959 | 0.1162 |
+| 0.2169        | 54.9986 | 19827 | 1.1406          | 0.3951 | 0.1150 |
+| 0.2186        | 56.0    | 20188 | 1.1512          | 0.3952 | 0.1164 |
+| 0.2221        | 56.9986 | 20548 | 1.1636          | 0.3945 | 0.1159 |
+| 0.2113        | 58.0    | 20909 | 1.1598          | 0.3935 | 0.1151 |
+| 0.2033        | 58.9986 | 21269 | 1.1667          | 0.3929 | 0.1154 |
+| 0.201         | 60.0    | 21630 | 1.1330          | 0.3902 | 0.1142 |
+| 0.2049        | 60.9986 | 21990 | 1.1746          | 0.3905 | 0.1138 |
+| 0.2043        | 62.0    | 22351 | 1.1990          | 0.3869 | 0.1133 |
+| 0.1945        | 62.9986 | 22711 | 1.1931          | 0.3900 | 0.1138 |
+| 0.1876        | 64.0    | 23072 | 1.1713          | 0.3833 | 0.1131 |
+| 0.1842        | 64.9986 | 23432 | 1.1645          | 0.3832 | 0.1127 |
+| 0.1842        | 66.0    | 23793 | 1.1445          | 0.3844 | 0.1129 |
+| 0.1853        | 66.9986 | 24153 | 1.1917          | 0.3853 | 0.1125 |
+| 0.1745        | 68.0    | 24514 | 1.1785          | 0.3796 | 0.1121 |
+| 0.1703        | 68.9986 | 24874 | 1.1752          | 0.3815 | 0.1114 |
+| 0.1711        | 70.0    | 25235 | 1.1820          | 0.3784 | 0.1107 |
+| 0.1687        | 70.9986 | 25595 | 1.1864          | 0.3788 | 0.1105 |
+| 0.1632        | 72.0    | 25956 | 1.2335          | 0.3758 | 0.1097 |
+| 0.1613        | 72.9986 | 26316 | 1.1948          | 0.3753 | 0.1099 |
+| 0.1551        | 74.0    | 26677 | 1.2681          | 0.3767 | 0.1098 |
+| 0.1606        | 74.9986 | 27037 | 1.2648          | 0.3738 | 0.1098 |
+| 0.1445        | 76.0    | 27398 | 1.2243          | 0.3739 | 0.1089 |
+| 0.1562        | 76.9986 | 27758 | 1.2221          | 0.3718 | 0.1089 |
+| 0.1457        | 78.0    | 28119 | 1.2586          | 0.3709 | 0.1081 |
+| 0.1431        | 78.9986 | 28479 | 1.2694          | 0.3731 | 0.1093 |
+| 0.138         | 80.0    | 28840 | 1.2734          | 0.3707 | 0.1092 |
+| 0.1382        | 80.9986 | 29200 | 1.2558          | 0.3668 | 0.1078 |
+| 0.1389        | 82.0    | 29561 | 1.2251          | 0.3683 | 0.1088 |
+| 0.1365        | 82.9986 | 29921 | 1.2232          | 0.3663 | 0.1081 |
+| 0.13          | 84.0    | 30282 | 1.2646          | 0.3663 | 0.1079 |
+| 0.1302        | 84.9986 | 30642 | 1.2837          | 0.3649 | 0.1073 |
+| 0.1262        | 86.0    | 31003 | 1.2755          | 0.3636 | 0.1063 |
+| 0.1276        | 86.9986 | 31363 | 1.2917          | 0.3637 | 0.1068 |
+| 0.1217        | 88.0    | 31724 | 1.2952          | 0.3623 | 0.1064 |
+| 0.1228        | 88.9986 | 32084 | 1.2751          | 0.3602 | 0.1057 |
+| 0.1196        | 90.0    | 32445 | 1.2764          | 0.3606 | 0.1056 |
+| 0.1214        | 90.9986 | 32805 | 1.2727          | 0.3603 | 0.1057 |
+| 0.1212        | 92.0    | 33166 | 1.2687          | 0.3582 | 0.1051 |
+| 0.1157        | 92.9986 | 33526 | 1.2731          | 0.3576 | 0.1050 |
+| 0.1134        | 94.0    | 33887 | 1.2842          | 0.3580 | 0.1052 |
+| 0.1119        | 94.9986 | 34247 | 1.3028          | 0.3572 | 0.1051 |
+| 0.1132        | 96.0    | 34608 | 1.2819          | 0.3562 | 0.1047 |
+| 0.1117        | 96.9986 | 34968 | 1.2993          | 0.3561 | 0.1047 |
+| 0.1078        | 98.0    | 35329 | 1.3051          | 0.3547 | 0.1045 |
+| 0.1088        | 98.9986 | 35689 | 1.2980          | 0.3554 | 0.1043 |
+| 0.1066        | 99.8613 | 36000 | 1.2971          | 0.3556 | 0.1044 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.1.0+cu118
+- Datasets 3.1.0
+- Tokenizers 0.20.1

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