asr-africa
/

w2v-bert-2.0-yogera-lg-26hrs-v1

@@ -1,199 +1,114 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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-## Model Details
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 ---
 library_name: transformers
+language:
+- lg
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+datasets:
+- yogera
+metrics:
+- wer
+model-index:
+- name: wav2vec2-bert
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Yogera
+      type: yogera
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.12906588824020016
 ---
+<!-- 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-bert
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the Yogera dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2157
+- Wer: 0.1291
+- Cer: 0.0296
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 0.6428        | 1.0   | 257  | 0.1958          | 0.2392 | 0.0488 |
+| 0.1608        | 2.0   | 514  | 0.1623          | 0.1868 | 0.0393 |
+| 0.1216        | 3.0   | 771  | 0.1471          | 0.1663 | 0.0368 |
+| 0.1001        | 4.0   | 1028 | 0.1483          | 0.1601 | 0.0351 |
+| 0.0859        | 5.0   | 1285 | 0.1471          | 0.1497 | 0.0332 |
+| 0.0742        | 6.0   | 1542 | 0.1478          | 0.1468 | 0.0315 |
+| 0.0641        | 7.0   | 1799 | 0.1642          | 0.1476 | 0.0326 |
+| 0.0544        | 8.0   | 2056 | 0.1520          | 0.1461 | 0.0322 |
+| 0.0489        | 9.0   | 2313 | 0.1596          | 0.1386 | 0.0312 |
+| 0.0452        | 10.0  | 2570 | 0.1521          | 0.1408 | 0.0320 |
+| 0.04          | 11.0  | 2827 | 0.1754          | 0.1395 | 0.0306 |
+| 0.0371        | 12.0  | 3084 | 0.1703          | 0.1405 | 0.0309 |
+| 0.0329        | 13.0  | 3341 | 0.1657          | 0.1447 | 0.0318 |
+| 0.0323        | 14.0  | 3598 | 0.1695          | 0.1327 | 0.0298 |
+| 0.0282        | 15.0  | 3855 | 0.1852          | 0.1356 | 0.0310 |
+| 0.0237        | 16.0  | 4112 | 0.1728          | 0.1399 | 0.0308 |
+| 0.0229        | 17.0  | 4369 | 0.1810          | 0.1301 | 0.0291 |
+| 0.02          | 18.0  | 4626 | 0.1781          | 0.1367 | 0.0304 |
+| 0.0204        | 19.0  | 4883 | 0.2039          | 0.1329 | 0.0293 |
+| 0.0186        | 20.0  | 5140 | 0.1929          | 0.1366 | 0.0302 |
+| 0.0164        | 21.0  | 5397 | 0.2022          | 0.1356 | 0.0301 |
+| 0.0154        | 22.0  | 5654 | 0.1787          | 0.1307 | 0.0293 |
+| 0.0127        | 23.0  | 5911 | 0.2086          | 0.1296 | 0.0290 |
+| 0.0129        | 24.0  | 6168 | 0.2094          | 0.1281 | 0.0287 |
+| 0.0108        | 25.0  | 6425 | 0.2148          | 0.1254 | 0.0280 |
+| 0.0122        | 26.0  | 6682 | 0.2091          | 0.1339 | 0.0305 |
+| 0.0106        | 27.0  | 6939 | 0.2030          | 0.1315 | 0.0295 |
+| 0.0102        | 28.0  | 7196 | 0.2092          | 0.1241 | 0.0282 |
+| 0.0088        | 29.0  | 7453 | 0.2078          | 0.1290 | 0.0287 |
+| 0.008         | 30.0  | 7710 | 0.2112          | 0.1298 | 0.0282 |
+| 0.0084        | 31.0  | 7967 | 0.1972          | 0.1305 | 0.0295 |
+| 0.0074        | 32.0  | 8224 | 0.2130          | 0.1337 | 0.0293 |
+| 0.0062        | 33.0  | 8481 | 0.2141          | 0.1308 | 0.0297 |
+| 0.0065        | 34.0  | 8738 | 0.2151          | 0.1319 | 0.0296 |
+| 0.0079        | 35.0  | 8995 | 0.2070          | 0.1253 | 0.0279 |
+| 0.0059        | 36.0  | 9252 | 0.2229          | 0.1267 | 0.0285 |
+| 0.0071        | 37.0  | 9509 | 0.2218          | 0.1295 | 0.0297 |
+| 0.0066        | 38.0  | 9766 | 0.2157          | 0.1291 | 0.0296 |
+### Framework versions
+- Transformers 4.45.2
+- Pytorch 2.1.0+cu118
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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