End of training

README.md

@@ -0,0 +1,194 @@
+---
+library_name: transformers
+language:
+- lg
+base_model: asr-africa/wav2vec2-asr-africa-base
+tags:
+- asr
+- luganda
+- wav2vec2-base
+- speech
+- asr-africa
+- robust-fine-tuning
+- lg
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+- google/fleurs
+metrics:
+- wer
+model-index:
+- name: Wav2Vec2-Base - Luganda - asr-africa
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: mozilla-foundation/common_voice_17_0
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.1883851956379634
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: fleurs
+      type: google/fleurs
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.1883851956379634
+---
+
+<!-- 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-Base - Luganda - asr-africa
+
+This model is a fine-tuned version of [asr-africa/wav2vec2-asr-africa-base](https://huggingface.co/asr-africa/wav2vec2-asr-africa-base) on the common_voice_17_0 and the fleurs datasets.
+It achieves the following results on the evaluation set:
+- Loss: 0.1244
+- Wer: 0.1884
+- Cer: 0.0350
+
+## 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: 7e-05
+- train_batch_size: 64
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 100.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step   | Cer    | Validation Loss | Wer    |
+|:-------------:|:-----:|:------:|:------:|:---------------:|:------:|
+| 3.2575        | 1.0   | 3012   | 0.1093 | 0.3726          | 0.5341 |
+| 0.8396        | 2.0   | 6024   | 0.0781 | 0.2538          | 0.3984 |
+| 0.7487        | 3.0   | 9036   | 0.0682 | 0.2277          | 0.3531 |
+| 0.7226        | 4.0   | 12048  | 0.0643 | 0.2133          | 0.3364 |
+| 0.7096        | 5.0   | 15060  | 0.0612 | 0.2084          | 0.3211 |
+| 0.6979        | 6.0   | 18072  | 0.0640 | 0.2091          | 0.3287 |
+| 0.6899        | 7.0   | 21084  | 0.0608 | 0.2019          | 0.3162 |
+| 0.6765        | 8.0   | 24096  | 0.0601 | 0.1973          | 0.3106 |
+| 0.6701        | 9.0   | 27108  | 0.0582 | 0.1928          | 0.3047 |
+| 0.6621        | 10.0  | 30120  | 0.0582 | 0.1924          | 0.3039 |
+| 0.6554        | 11.0  | 33132  | 0.0566 | 0.1867          | 0.2983 |
+| 0.6475        | 12.0  | 36144  | 0.0552 | 0.1829          | 0.2874 |
+| 0.6429        | 13.0  | 39156  | 0.0542 | 0.1802          | 0.2853 |
+| 0.6351        | 14.0  | 42168  | 0.0553 | 0.1826          | 0.2873 |
+| 0.6319        | 15.0  | 45180  | 0.0544 | 0.1793          | 0.2832 |
+| 0.6251        | 16.0  | 48192  | 0.0548 | 0.1785          | 0.2838 |
+| 0.6172        | 17.0  | 51204  | 0.0517 | 0.1709          | 0.2719 |
+| 0.6122        | 18.0  | 54216  | 0.0521 | 0.1720          | 0.2716 |
+| 0.6068        | 19.0  | 57228  | 0.0505 | 0.1694          | 0.2665 |
+| 0.6035        | 20.0  | 60240  | 0.0497 | 0.1670          | 0.2628 |
+| 0.5957        | 21.0  | 63252  | 0.0504 | 0.1704          | 0.2644 |
+| 0.5909        | 22.0  | 66264  | 0.0493 | 0.1653          | 0.2599 |
+| 0.5879        | 23.0  | 69276  | 0.0487 | 0.1675          | 0.2573 |
+| 0.5966        | 24.0  | 72288  | 0.0510 | 0.1943          | 0.2739 |
+| 0.6444        | 25.0  | 75300  | 0.0515 | 0.1868          | 0.2723 |
+| 0.5999        | 26.0  | 78312  | 0.0491 | 0.1677          | 0.2578 |
+| 0.5911        | 27.0  | 81324  | 0.0474 | 0.1679          | 0.2510 |
+| 0.586         | 28.0  | 84336  | 0.0484 | 0.1723          | 0.2539 |
+| 0.5816        | 29.0  | 87348  | 0.0477 | 0.1678          | 0.2526 |
+| 0.5886        | 30.0  | 90360  | 0.0499 | 0.1824          | 0.2629 |
+| 0.5978        | 31.0  | 93372  | 0.0470 | 0.1620          | 0.2491 |
+| 0.5722        | 32.0  | 96384  | 0.0465 | 0.1584          | 0.2472 |
+| 0.5615        | 33.0  | 99396  | 0.0461 | 0.1564          | 0.2421 |
+| 0.5566        | 34.0  | 102408 | 0.0448 | 0.1530          | 0.2368 |
+| 0.5514        | 35.0  | 105420 | 0.0432 | 0.1499          | 0.2309 |
+| 0.5485        | 36.0  | 108432 | 0.0436 | 0.1511          | 0.2308 |
+| 0.5451        | 37.0  | 111444 | 0.0439 | 0.1507          | 0.2319 |
+| 0.5433        | 38.0  | 114456 | 0.0434 | 0.1482          | 0.2312 |
+| 0.5391        | 39.0  | 117468 | 0.0435 | 0.1468          | 0.2291 |
+| 0.5347        | 40.0  | 120480 | 0.0430 | 0.1463          | 0.2274 |
+| 0.5313        | 41.0  | 123492 | 0.0422 | 0.1450          | 0.2240 |
+| 0.5291        | 42.0  | 126504 | 0.0419 | 0.1446          | 0.2241 |
+| 0.5269        | 43.0  | 129516 | 0.0427 | 0.1453          | 0.2255 |
+| 0.5253        | 44.0  | 132528 | 0.0425 | 0.1446          | 0.2253 |
+| 0.523         | 45.0  | 135540 | 0.0412 | 0.1430          | 0.2202 |
+| 0.5192        | 46.0  | 138552 | 0.0409 | 0.1414          | 0.2172 |
+| 0.518         | 47.0  | 141564 | 0.0405 | 0.1404          | 0.2160 |
+| 0.5139        | 48.0  | 144576 | 0.0401 | 0.1400          | 0.2143 |
+| 0.5133        | 49.0  | 147588 | 0.0412 | 0.1414          | 0.2180 |
+| 0.5114        | 50.0  | 150600 | 0.0404 | 0.1402          | 0.2149 |
+| 0.5087        | 51.0  | 153612 | 0.0406 | 0.1404          | 0.2165 |
+| 0.5066        | 52.0  | 156624 | 0.0404 | 0.1389          | 0.2157 |
+| 0.5037        | 53.0  | 159636 | 0.0398 | 0.1375          | 0.2132 |
+| 0.5024        | 54.0  | 162648 | 0.0398 | 0.1372          | 0.2121 |
+| 0.5           | 55.0  | 165660 | 0.0401 | 0.1379          | 0.2132 |
+| 0.4976        | 56.0  | 168672 | 0.0386 | 0.1349          | 0.2072 |
+| 0.4948        | 57.0  | 171684 | 0.0393 | 0.1362          | 0.2102 |
+| 0.4933        | 58.0  | 174696 | 0.0389 | 0.1355          | 0.2068 |
+| 0.4924        | 59.0  | 177708 | 0.0385 | 0.1361          | 0.2055 |
+| 0.4901        | 60.0  | 180720 | 0.0384 | 0.1346          | 0.2054 |
+| 0.4898        | 61.0  | 183732 | 0.0384 | 0.1334          | 0.2050 |
+| 0.4873        | 62.0  | 186744 | 0.0384 | 0.1342          | 0.2060 |
+| 0.4865        | 63.0  | 189756 | 0.0387 | 0.1346          | 0.2070 |
+| 0.4842        | 64.0  | 192768 | 0.0387 | 0.1346          | 0.2072 |
+| 0.4822        | 65.0  | 195780 | 0.0381 | 0.1325          | 0.2040 |
+| 0.4814        | 66.0  | 198792 | 0.0371 | 0.1312          | 0.1989 |
+| 0.4796        | 67.0  | 201804 | 0.0374 | 0.1312          | 0.2000 |
+| 0.4771        | 68.0  | 204816 | 0.0372 | 0.1304          | 0.1997 |
+| 0.4756        | 69.0  | 207828 | 0.0377 | 0.1308          | 0.2009 |
+| 0.4745        | 70.0  | 210840 | 0.0370 | 0.1312          | 0.1982 |
+| 0.4738        | 71.0  | 213852 | 0.0374 | 0.1307          | 0.2001 |
+| 0.473         | 72.0  | 216864 | 0.0372 | 0.1307          | 0.1991 |
+| 0.472         | 73.0  | 219876 | 0.0366 | 0.1292          | 0.1961 |
+| 0.4693        | 74.0  | 222888 | 0.0364 | 0.1287          | 0.1952 |
+| 0.4693        | 75.0  | 225900 | 0.0363 | 0.1284          | 0.1945 |
+| 0.4664        | 76.0  | 228912 | 0.0368 | 0.1288          | 0.1969 |
+| 0.4651        | 77.0  | 231924 | 0.0368 | 0.1287          | 0.1971 |
+| 0.4641        | 78.0  | 234936 | 0.0366 | 0.1287          | 0.1952 |
+| 0.462         | 79.0  | 237948 | 0.0364 | 0.1287          | 0.1945 |
+| 0.4608        | 80.0  | 240960 | 0.0363 | 0.1275          | 0.1952 |
+| 0.4594        | 81.0  | 243972 | 0.0361 | 0.1277          | 0.1939 |
+| 0.4595        | 82.0  | 246984 | 0.0359 | 0.1268          | 0.1937 |
+| 0.4575        | 83.0  | 249996 | 0.0362 | 0.1272          | 0.1942 |
+| 0.4569        | 84.0  | 253008 | 0.1268 | 0.1934          | 0.0361 |
+| 0.4552        | 85.0  | 256020 | 0.1262 | 0.1916          | 0.0357 |
+| 0.4538        | 86.0  | 259032 | 0.1259 | 0.1907          | 0.0355 |
+| 0.4532        | 87.0  | 262044 | 0.1258 | 0.1912          | 0.0355 |
+| 0.4524        | 88.0  | 265056 | 0.1260 | 0.1910          | 0.0356 |
+| 0.4501        | 89.0  | 268068 | 0.1266 | 0.1928          | 0.0360 |
+| 0.4491        | 90.0  | 271080 | 0.1252 | 0.1904          | 0.0355 |
+| 0.4486        | 91.0  | 274092 | 0.1253 | 0.1889          | 0.0352 |
+| 0.4487        | 92.0  | 277104 | 0.1253 | 0.1902          | 0.0354 |
+| 0.4471        | 93.0  | 280116 | 0.1252 | 0.1894          | 0.0352 |
+| 0.4458        | 94.0  | 283128 | 0.1253 | 0.1891          | 0.0352 |
+| 0.4449        | 95.0  | 286140 | 0.1248 | 0.1884          | 0.0351 |
+| 0.4434        | 96.0  | 289152 | 0.1247 | 0.1891          | 0.0351 |
+| 0.4435        | 97.0  | 292164 | 0.1247 | 0.1891          | 0.0352 |
+| 0.4444        | 98.0  | 295176 | 0.1245 | 0.1888          | 0.0351 |
+| 0.4429        | 99.0  | 298188 | 0.1244 | 0.1887          | 0.0351 |
+| 0.4426        | 100.0 | 301200 | 0.1244 | 0.1884          | 0.0350 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.1

added_tokens.json

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checkpoint-298188/config.json

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+  "xvector_output_dim": 512
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