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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: 0.47644382219110953 |
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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: 0.2982 |
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- Model Preparation Time: 0.0133 |
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- Wer: 0.4764 |
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- Cer: 0.0937 |
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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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| 1.8637 | 0.9989 | 568 | 0.1607 | 0.0133 | 0.2395 | 0.0374 | |
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| 0.1869 | 1.9989 | 1136 | 0.1470 | 0.0133 | 0.2161 | 0.0338 | |
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| 0.1694 | 2.9989 | 1704 | 0.1361 | 0.0133 | 0.1968 | 0.0311 | |
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| 0.153 | 3.9989 | 2272 | 0.1263 | 0.0133 | 0.1840 | 0.0294 | |
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| 0.1413 | 4.9989 | 2840 | 0.1232 | 0.0133 | 0.1727 | 0.0278 | |
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| 0.1359 | 5.9989 | 3408 | 0.1170 | 0.0133 | 0.1675 | 0.0268 | |
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| 0.1271 | 6.9989 | 3976 | 0.1132 | 0.0133 | 0.1623 | 0.0264 | |
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| 0.1202 | 7.9989 | 4544 | 0.1102 | 0.0133 | 0.1570 | 0.0254 | |
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| 0.1161 | 8.9989 | 5112 | 0.1105 | 0.0133 | 0.1549 | 0.0251 | |
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| 0.111 | 9.9989 | 5680 | 0.1036 | 0.0133 | 0.1501 | 0.0244 | |
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| 0.1075 | 10.9989 | 6248 | 0.1022 | 0.0133 | 0.1429 | 0.0235 | |
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| 0.1036 | 11.9989 | 6816 | 0.1016 | 0.0133 | 0.1414 | 0.0233 | |
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| 0.0992 | 12.9989 | 7384 | 0.1009 | 0.0133 | 0.1387 | 0.0227 | |
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| 0.0951 | 13.9989 | 7952 | 0.0986 | 0.0133 | 0.1370 | 0.0224 | |
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| 0.0931 | 14.9989 | 8520 | 0.0964 | 0.0133 | 0.1331 | 0.0221 | |
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| 0.0901 | 15.9989 | 9088 | 0.0958 | 0.0133 | 0.1296 | 0.0215 | |
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| 0.0887 | 16.9989 | 9656 | 0.0942 | 0.0133 | 0.1304 | 0.0214 | |
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| 0.0845 | 17.9989 | 10224 | 0.0935 | 0.0133 | 0.1247 | 0.0208 | |
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| 0.082 | 18.9989 | 10792 | 0.0938 | 0.0133 | 0.1234 | 0.0206 | |
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| 0.079 | 19.9989 | 11360 | 0.0922 | 0.0133 | 0.1229 | 0.0206 | |
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| 0.0773 | 20.9989 | 11928 | 0.0900 | 0.0133 | 0.1191 | 0.0199 | |
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| 0.0749 | 21.9989 | 12496 | 0.0907 | 0.0133 | 0.1191 | 0.0199 | |
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| 0.0732 | 22.9989 | 13064 | 0.0911 | 0.0133 | 0.1188 | 0.0198 | |
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| 0.0714 | 23.9989 | 13632 | 0.0883 | 0.0133 | 0.1157 | 0.0194 | |
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| 0.0687 | 24.9989 | 14200 | 0.0909 | 0.0133 | 0.1180 | 0.0197 | |
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| 0.0676 | 25.9989 | 14768 | 0.0889 | 0.0133 | 0.1072 | 0.0182 | |
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| 0.0659 | 26.9989 | 15336 | 0.0875 | 0.0133 | 0.1109 | 0.0185 | |
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| 0.0632 | 27.9989 | 15904 | 0.0876 | 0.0133 | 0.1071 | 0.0183 | |
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| 0.0626 | 28.9989 | 16472 | 0.0894 | 0.0133 | 0.1099 | 0.0184 | |
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| 0.0606 | 29.9989 | 17040 | 0.0845 | 0.0133 | 0.1036 | 0.0176 | |
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| 0.0583 | 30.9989 | 17608 | 0.0901 | 0.0133 | 0.1073 | 0.0181 | |
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| 0.057 | 31.9989 | 18176 | 0.0879 | 0.0133 | 0.1021 | 0.0174 | |
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| 0.0562 | 32.9989 | 18744 | 0.0878 | 0.0133 | 0.1042 | 0.0179 | |
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| 0.0556 | 33.9989 | 19312 | 0.0878 | 0.0133 | 0.1023 | 0.0175 | |
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| 0.0543 | 34.9989 | 19880 | 0.0825 | 0.0133 | 0.0983 | 0.0167 | |
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| 0.0531 | 35.9989 | 20448 | 0.0846 | 0.0133 | 0.0982 | 0.0167 | |
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| 0.0513 | 36.9989 | 21016 | 0.0858 | 0.0133 | 0.1010 | 0.0171 | |
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| 0.0499 | 37.9989 | 21584 | 0.0878 | 0.0133 | 0.1002 | 0.0168 | |
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| 0.0492 | 38.9989 | 22152 | 0.0872 | 0.0133 | 0.0988 | 0.0166 | |
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| 0.0474 | 39.9989 | 22720 | 0.0863 | 0.0133 | 0.0964 | 0.0166 | |
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| 0.0467 | 40.9989 | 23288 | 0.0877 | 0.0133 | 0.0986 | 0.0167 | |
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| 0.0455 | 41.9989 | 23856 | 0.0897 | 0.0133 | 0.0969 | 0.0167 | |
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| 0.0454 | 42.9989 | 24424 | 0.0892 | 0.0133 | 0.0960 | 0.0164 | |
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| 0.0437 | 43.9989 | 24992 | 0.0897 | 0.0133 | 0.0979 | 0.0168 | |
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| 0.0423 | 44.9989 | 25560 | 0.0888 | 0.0133 | 0.0924 | 0.0159 | |
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| 0.0415 | 45.9989 | 26128 | 0.0899 | 0.0133 | 0.0919 | 0.0160 | |
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| 0.0412 | 46.9989 | 26696 | 0.0906 | 0.0133 | 0.0934 | 0.0161 | |
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| 0.0397 | 47.9989 | 27264 | 0.0854 | 0.0133 | 0.0889 | 0.0153 | |
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| 0.0388 | 48.9989 | 27832 | 0.0904 | 0.0133 | 0.0936 | 0.0160 | |
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| 0.0386 | 49.9989 | 28400 | 0.0903 | 0.0133 | 0.0892 | 0.0156 | |
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| 0.0381 | 50.9989 | 28968 | 0.0879 | 0.0133 | 0.0921 | 0.0160 | |
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| 0.0378 | 51.9989 | 29536 | 0.0876 | 0.0133 | 0.0893 | 0.0155 | |
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| 0.0378 | 52.9989 | 30104 | 0.0887 | 0.0133 | 0.0889 | 0.0155 | |
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| 0.0353 | 53.9989 | 30672 | 0.0902 | 0.0133 | 0.0887 | 0.0155 | |
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| 0.0351 | 54.9989 | 31240 | 0.0904 | 0.0133 | 0.0911 | 0.0158 | |
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| 0.0332 | 55.9989 | 31808 | 0.0881 | 0.0133 | 0.0854 | 0.0151 | |
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| 0.0349 | 56.9989 | 32376 | 0.0892 | 0.0133 | 0.0903 | 0.0155 | |
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| 0.0339 | 57.9989 | 32944 | 0.0919 | 0.0133 | 0.0876 | 0.0154 | |
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| 0.032 | 58.9989 | 33512 | 0.0892 | 0.0133 | 0.0862 | 0.0148 | |
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| 0.0316 | 59.9989 | 34080 | 0.0881 | 0.0133 | 0.0831 | 0.0149 | |
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| 0.0304 | 60.9989 | 34648 | 0.0892 | 0.0133 | 0.0830 | 0.0147 | |
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| 0.0314 | 61.9989 | 35216 | 0.0880 | 0.0133 | 0.0856 | 0.0151 | |
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| 0.0317 | 62.9989 | 35784 | 0.0891 | 0.0133 | 0.0870 | 0.0149 | |
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| 0.0304 | 63.9989 | 36352 | 0.0883 | 0.0133 | 0.0825 | 0.0148 | |
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| 0.0298 | 64.9989 | 36920 | 0.0923 | 0.0133 | 0.0839 | 0.0148 | |
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| 0.0303 | 65.9989 | 37488 | 0.0909 | 0.0133 | 0.0841 | 0.0147 | |
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| 0.0297 | 66.9989 | 38056 | 0.0906 | 0.0133 | 0.0845 | 0.0148 | |
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| 0.0293 | 67.9989 | 38624 | 0.0921 | 0.0133 | 0.0843 | 0.0147 | |
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| 0.0279 | 68.9989 | 39192 | 0.0934 | 0.0133 | 0.0823 | 0.0144 | |
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| 0.0268 | 69.9989 | 39760 | 0.0935 | 0.0133 | 0.0833 | 0.0144 | |
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### Framework versions |
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- Transformers 4.47.0 |
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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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