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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: facebook/mms-1b-all |
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tags: |
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- automatic-speech-recognition |
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- swagen |
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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-1b-swagen-female-model |
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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-1b-swagen-female-model |
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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 SWAGEN - SWA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2065 |
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- Wer: 0.1900 |
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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: 4 |
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- seed: 42 |
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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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- training_steps: 2500 |
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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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| 8.5907 | 0.1176 | 100 | 4.5590 | 1.0 | |
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| 4.3006 | 0.2353 | 200 | 4.2573 | 1.0 | |
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| 4.1906 | 0.3529 | 300 | 3.8436 | 1.0 | |
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| 1.1198 | 0.4706 | 400 | 0.2569 | 0.1996 | |
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| 0.3012 | 0.5882 | 500 | 0.2466 | 0.1942 | |
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| 0.2919 | 0.7059 | 600 | 0.2501 | 0.1990 | |
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| 0.267 | 0.8235 | 700 | 0.2353 | 0.1894 | |
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| 0.2666 | 0.9412 | 800 | 0.2280 | 0.1904 | |
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| 0.2396 | 1.0588 | 900 | 0.2238 | 0.1892 | |
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| 0.258 | 1.1765 | 1000 | 0.2202 | 0.1898 | |
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| 0.2192 | 1.2941 | 1100 | 0.2196 | 0.1938 | |
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| 0.2353 | 1.4118 | 1200 | 0.2169 | 0.1875 | |
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| 0.2398 | 1.5294 | 1300 | 0.2164 | 0.1896 | |
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| 0.2419 | 1.6471 | 1400 | 0.2146 | 0.1913 | |
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| 0.2582 | 1.7647 | 1500 | 0.2122 | 0.1905 | |
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| 0.2417 | 1.8824 | 1600 | 0.2105 | 0.1861 | |
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| 0.2375 | 2.0 | 1700 | 0.2091 | 0.1892 | |
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| 0.2353 | 2.1176 | 1800 | 0.2087 | 0.1882 | |
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| 0.23 | 2.2353 | 1900 | 0.2091 | 0.1904 | |
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| 0.2378 | 2.3529 | 2000 | 0.2067 | 0.1898 | |
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| 0.2343 | 2.4706 | 2100 | 0.2061 | 0.1890 | |
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| 0.2083 | 2.5882 | 2200 | 0.2084 | 0.1884 | |
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| 0.2058 | 2.7059 | 2300 | 0.2085 | 0.1882 | |
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| 0.2197 | 2.8235 | 2400 | 0.2062 | 0.1904 | |
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| 0.2317 | 2.9412 | 2500 | 0.2065 | 0.1896 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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