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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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