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--- |
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library_name: transformers |
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language: |
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- zul |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- NCHLT_speech_corpus |
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metrics: |
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- wer |
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model-index: |
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- name: facebook mms-1b-all zulu - Beijuka Bruno |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: NCHLT_speech_corpus/Zulu |
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type: NCHLT_speech_corpus |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3831991599579979 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# facebook mms-1b-all zulu - Beijuka Bruno |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NCHLT_speech_corpus/Zulu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2668 |
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- Model Preparation Time: 0.0161 |
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- Wer: 0.3832 |
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- Cer: 0.0671 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:| |
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| 75.5144 | 1.0 | 139 | 0.6716 | 0.0161 | 0.6021 | 0.1091 | |
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| 2.2356 | 2.0 | 278 | 0.1570 | 0.0161 | 0.2587 | 0.0378 | |
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| 1.6751 | 3.0 | 417 | 0.1414 | 0.0161 | 0.2355 | 0.0342 | |
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| 1.5484 | 4.0 | 556 | 0.1314 | 0.0161 | 0.2148 | 0.0308 | |
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| 1.4406 | 5.0 | 695 | 0.1275 | 0.0161 | 0.2100 | 0.0301 | |
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| 1.3547 | 6.0 | 834 | 0.1247 | 0.0161 | 0.1967 | 0.0288 | |
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| 1.3095 | 7.0 | 973 | 0.1191 | 0.0161 | 0.1909 | 0.0277 | |
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| 1.2359 | 8.0 | 1112 | 0.1176 | 0.0161 | 0.1865 | 0.0271 | |
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| 1.1879 | 9.0 | 1251 | 0.1173 | 0.0161 | 0.1818 | 0.0269 | |
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| 1.1513 | 10.0 | 1390 | 0.1181 | 0.0161 | 0.1818 | 0.0267 | |
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| 1.1037 | 11.0 | 1529 | 0.1145 | 0.0161 | 0.1797 | 0.0258 | |
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| 1.0629 | 12.0 | 1668 | 0.1090 | 0.0161 | 0.1726 | 0.0253 | |
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| 1.0302 | 13.0 | 1807 | 0.1087 | 0.0161 | 0.1705 | 0.0249 | |
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| 0.9804 | 14.0 | 1946 | 0.1059 | 0.0161 | 0.1654 | 0.0243 | |
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| 0.9649 | 15.0 | 2085 | 0.1098 | 0.0161 | 0.1644 | 0.0242 | |
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| 0.9074 | 16.0 | 2224 | 0.1052 | 0.0161 | 0.1624 | 0.0239 | |
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| 0.8947 | 17.0 | 2363 | 0.1045 | 0.0161 | 0.1579 | 0.0236 | |
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| 0.8442 | 18.0 | 2502 | 0.1063 | 0.0161 | 0.1572 | 0.0233 | |
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| 0.8151 | 19.0 | 2641 | 0.1036 | 0.0161 | 0.1566 | 0.0230 | |
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| 0.809 | 20.0 | 2780 | 0.1046 | 0.0161 | 0.1583 | 0.0234 | |
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| 0.8049 | 21.0 | 2919 | 0.1055 | 0.0161 | 0.1596 | 0.0229 | |
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| 0.7888 | 22.0 | 3058 | 0.1037 | 0.0161 | 0.1521 | 0.0221 | |
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| 0.7426 | 23.0 | 3197 | 0.1052 | 0.0161 | 0.1521 | 0.0223 | |
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| 0.7328 | 24.0 | 3336 | 0.1033 | 0.0161 | 0.1477 | 0.0221 | |
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| 0.7215 | 25.0 | 3475 | 0.1046 | 0.0161 | 0.1521 | 0.0224 | |
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| 0.6755 | 26.0 | 3614 | 0.1053 | 0.0161 | 0.1515 | 0.0225 | |
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| 0.6844 | 27.0 | 3753 | 0.1016 | 0.0161 | 0.1464 | 0.0217 | |
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| 0.6419 | 28.0 | 3892 | 0.1042 | 0.0161 | 0.1453 | 0.0214 | |
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| 0.6459 | 29.0 | 4031 | 0.1029 | 0.0161 | 0.1436 | 0.0209 | |
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| 0.6528 | 30.0 | 4170 | 0.1020 | 0.0161 | 0.1423 | 0.0214 | |
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| 0.6177 | 31.0 | 4309 | 0.1037 | 0.0161 | 0.1430 | 0.0213 | |
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| 0.5899 | 32.0 | 4448 | 0.1042 | 0.0161 | 0.1487 | 0.0225 | |
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| 0.6216 | 33.0 | 4587 | 0.1064 | 0.0161 | 0.1416 | 0.0212 | |
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| 0.5864 | 34.0 | 4726 | 0.1071 | 0.0161 | 0.1443 | 0.0217 | |
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| 0.5797 | 35.0 | 4865 | 0.1032 | 0.0161 | 0.1467 | 0.0215 | |
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| 0.5562 | 36.0 | 5004 | 0.1059 | 0.0161 | 0.1433 | 0.0213 | |
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| 0.5575 | 37.0 | 5143 | 0.1039 | 0.0161 | 0.1440 | 0.0214 | |
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| 0.5236 | 38.0 | 5282 | 0.1036 | 0.0161 | 0.1382 | 0.0207 | |
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| 0.5128 | 39.0 | 5421 | 0.1021 | 0.0161 | 0.1385 | 0.0203 | |
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| 0.4987 | 40.0 | 5560 | 0.1032 | 0.0161 | 0.1430 | 0.0208 | |
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| 0.5254 | 41.0 | 5699 | 0.1056 | 0.0161 | 0.1355 | 0.0204 | |
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| 0.5086 | 42.0 | 5838 | 0.1038 | 0.0161 | 0.1406 | 0.0206 | |
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| 0.4772 | 43.0 | 5977 | 0.1075 | 0.0161 | 0.1402 | 0.0205 | |
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| 0.4541 | 44.0 | 6116 | 0.1050 | 0.0161 | 0.1355 | 0.0200 | |
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| 0.4791 | 45.0 | 6255 | 0.1066 | 0.0161 | 0.1324 | 0.0198 | |
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| 0.4764 | 46.0 | 6394 | 0.1038 | 0.0161 | 0.1358 | 0.0198 | |
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| 0.4556 | 47.0 | 6533 | 0.1043 | 0.0161 | 0.1334 | 0.0197 | |
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| 0.4485 | 48.0 | 6672 | 0.1041 | 0.0161 | 0.1321 | 0.0195 | |
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| 0.44 | 49.0 | 6811 | 0.1071 | 0.0161 | 0.1385 | 0.0204 | |
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| 0.4265 | 50.0 | 6950 | 0.1086 | 0.0161 | 0.1361 | 0.0201 | |
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| 0.4388 | 51.0 | 7089 | 0.1066 | 0.0161 | 0.1304 | 0.0195 | |
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| 0.4326 | 52.0 | 7228 | 0.1087 | 0.0161 | 0.1331 | 0.0201 | |
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| 0.3916 | 53.0 | 7367 | 0.1091 | 0.0161 | 0.1368 | 0.0203 | |
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| 0.396 | 54.0 | 7506 | 0.1125 | 0.0161 | 0.1324 | 0.0198 | |
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| 0.4223 | 55.0 | 7645 | 0.1104 | 0.0161 | 0.1310 | 0.0195 | |
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| 0.3937 | 56.0 | 7784 | 0.1093 | 0.0161 | 0.1293 | 0.0193 | |
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| 0.4038 | 57.0 | 7923 | 0.1145 | 0.0161 | 0.1317 | 0.0197 | |
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| 0.402 | 58.0 | 8062 | 0.1112 | 0.0161 | 0.1331 | 0.0199 | |
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| 0.3912 | 59.0 | 8201 | 0.1109 | 0.0161 | 0.1270 | 0.0190 | |
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| 0.3888 | 60.0 | 8340 | 0.1103 | 0.0161 | 0.1249 | 0.0188 | |
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| 0.3797 | 61.0 | 8479 | 0.1074 | 0.0161 | 0.1276 | 0.0191 | |
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| 0.3682 | 62.0 | 8618 | 0.1111 | 0.0161 | 0.1293 | 0.0194 | |
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| 0.3678 | 63.0 | 8757 | 0.1117 | 0.0161 | 0.1304 | 0.0191 | |
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| 0.3611 | 64.0 | 8896 | 0.1136 | 0.0161 | 0.1253 | 0.0191 | |
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| 0.3406 | 65.0 | 9035 | 0.1114 | 0.0161 | 0.1232 | 0.0186 | |
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| 0.328 | 66.0 | 9174 | 0.1101 | 0.0161 | 0.1246 | 0.0187 | |
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| 0.3482 | 67.0 | 9313 | 0.1103 | 0.0161 | 0.1205 | 0.0182 | |
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| 0.344 | 68.0 | 9452 | 0.1130 | 0.0161 | 0.1215 | 0.0183 | |
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| 0.3465 | 69.0 | 9591 | 0.1115 | 0.0161 | 0.1290 | 0.0191 | |
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| 0.3411 | 70.0 | 9730 | 0.1124 | 0.0161 | 0.1249 | 0.0186 | |
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| 0.3182 | 71.0 | 9869 | 0.1142 | 0.0161 | 0.1225 | 0.0182 | |
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| 0.3303 | 72.0 | 10008 | 0.1116 | 0.0161 | 0.1232 | 0.0183 | |
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| 0.3632 | 73.0 | 10147 | 0.1099 | 0.0161 | 0.1229 | 0.0184 | |
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| 0.3183 | 74.0 | 10286 | 0.1128 | 0.0161 | 0.1266 | 0.0190 | |
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| 0.3215 | 75.0 | 10425 | 0.1119 | 0.0161 | 0.1229 | 0.0184 | |
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| 0.3019 | 76.0 | 10564 | 0.1132 | 0.0161 | 0.1253 | 0.0184 | |
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| 0.3275 | 77.0 | 10703 | 0.1103 | 0.0161 | 0.1212 | 0.0182 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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