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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: mms-meta/mms-zeroshot-300m |
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tags: |
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- automatic-speech-recognition |
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- BembaSpeech |
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- mms |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: mms-zeroshot-bem-sv-male |
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results: [] |
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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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# mms-zeroshot-bem-sv-male |
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This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the BEMBASPEECH - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1874 |
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- Wer: 0.3949 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 10.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| No log | 0.2183 | 200 | 2.3822 | 1.0 | |
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| No log | 0.4367 | 400 | 0.2715 | 0.5093 | |
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| 2.7769 | 0.6550 | 600 | 0.2489 | 0.4820 | |
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| 2.7769 | 0.8734 | 800 | 0.2296 | 0.4695 | |
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| 0.6809 | 1.0917 | 1000 | 0.2209 | 0.4638 | |
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| 0.6809 | 1.3100 | 1200 | 0.2163 | 0.4469 | |
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| 0.6809 | 1.5284 | 1400 | 0.2092 | 0.4400 | |
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| 0.6113 | 1.7467 | 1600 | 0.2047 | 0.4346 | |
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| 0.6113 | 1.9651 | 1800 | 0.2074 | 0.4467 | |
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| 0.5974 | 2.1834 | 2000 | 0.2041 | 0.4304 | |
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| 0.5974 | 2.4017 | 2200 | 0.2054 | 0.4317 | |
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| 0.5974 | 2.6201 | 2400 | 0.1987 | 0.4240 | |
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| 0.5636 | 2.8384 | 2600 | 0.2003 | 0.4252 | |
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| 0.5636 | 3.0568 | 2800 | 0.1997 | 0.4287 | |
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| 0.5398 | 3.2751 | 3000 | 0.2097 | 0.4400 | |
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| 0.5398 | 3.4934 | 3200 | 0.1968 | 0.4165 | |
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| 0.5398 | 3.7118 | 3400 | 0.2013 | 0.4218 | |
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| 0.5334 | 3.9301 | 3600 | 0.2003 | 0.4230 | |
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| 0.5334 | 4.1485 | 3800 | 0.1976 | 0.4227 | |
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| 0.5123 | 4.3668 | 4000 | 0.1978 | 0.4198 | |
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| 0.5123 | 4.5852 | 4200 | 0.2019 | 0.4298 | |
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| 0.5123 | 4.8035 | 4400 | 0.1939 | 0.4146 | |
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| 0.5119 | 5.0218 | 4600 | 0.1989 | 0.4161 | |
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| 0.5119 | 5.2402 | 4800 | 0.1902 | 0.4076 | |
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| 0.4929 | 5.4585 | 5000 | 0.1929 | 0.4116 | |
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| 0.4929 | 5.6769 | 5200 | 0.1943 | 0.4144 | |
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| 0.4929 | 5.8952 | 5400 | 0.1922 | 0.4106 | |
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| 0.4878 | 6.1135 | 5600 | 0.1933 | 0.4137 | |
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| 0.4878 | 6.3319 | 5800 | 0.1920 | 0.4058 | |
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| 0.4755 | 6.5502 | 6000 | 0.1927 | 0.4171 | |
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| 0.4755 | 6.7686 | 6200 | 0.1920 | 0.4127 | |
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| 0.4755 | 6.9869 | 6400 | 0.1925 | 0.4061 | |
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| 0.475 | 7.2052 | 6600 | 0.1884 | 0.4058 | |
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| 0.475 | 7.4236 | 6800 | 0.1903 | 0.4070 | |
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| 0.4715 | 7.6419 | 7000 | 0.1882 | 0.3996 | |
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| 0.4715 | 7.8603 | 7200 | 0.1881 | 0.4033 | |
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| 0.4715 | 8.0786 | 7400 | 0.1885 | 0.4007 | |
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| 0.4575 | 8.2969 | 7600 | 0.1885 | 0.4016 | |
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| 0.4575 | 8.5153 | 7800 | 0.1888 | 0.4050 | |
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| 0.4611 | 8.7336 | 8000 | 0.1884 | 0.4046 | |
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| 0.4611 | 8.9520 | 8200 | 0.1881 | 0.3974 | |
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| 0.4611 | 9.1703 | 8400 | 0.1865 | 0.3956 | |
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| 0.4559 | 9.3886 | 8600 | 0.1875 | 0.3974 | |
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| 0.4559 | 9.6070 | 8800 | 0.1872 | 0.3996 | |
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| 0.4536 | 9.8253 | 9000 | 0.1876 | 0.3953 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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