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--- |
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language: |
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- ug |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: xls-r-uyghur-cv8 |
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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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# xls-r-uyghur-cv8 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UG dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2163 |
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- Wer: 0.3249 |
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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: 0.0001 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 2000 |
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- num_epochs: 100.0 |
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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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| 3.2914 | 4.85 | 500 | 3.2283 | 1.0 | |
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| 3.0068 | 9.71 | 1000 | 2.7939 | 0.9980 | |
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| 1.4306 | 14.56 | 1500 | 0.4857 | 0.6314 | |
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| 1.2831 | 19.42 | 2000 | 0.3679 | 0.6066 | |
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| 1.2065 | 24.27 | 2500 | 0.3303 | 0.5560 | |
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| 1.1449 | 29.13 | 3000 | 0.3008 | 0.4690 | |
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| 1.0926 | 33.98 | 3500 | 0.2817 | 0.4619 | |
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| 1.0635 | 38.83 | 4000 | 0.2665 | 0.4391 | |
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| 1.029 | 43.69 | 4500 | 0.2616 | 0.4175 | |
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| 1.0064 | 48.54 | 5000 | 0.2468 | 0.4051 | |
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| 0.9659 | 53.4 | 5500 | 0.2394 | 0.3860 | |
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| 0.9254 | 58.25 | 6000 | 0.2373 | 0.3689 | |
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| 0.9209 | 63.11 | 6500 | 0.2347 | 0.3670 | |
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| 0.889 | 67.96 | 7000 | 0.2291 | 0.3687 | |
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| 0.8859 | 72.82 | 7500 | 0.2272 | 0.3616 | |
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| 0.8441 | 77.67 | 8000 | 0.2232 | 0.3538 | |
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| 0.8284 | 82.52 | 8500 | 0.2224 | 0.3382 | |
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| 0.8142 | 87.38 | 9000 | 0.2193 | 0.3310 | |
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| 0.8012 | 92.23 | 9500 | 0.2168 | 0.3276 | |
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| 0.7781 | 97.09 | 10000 | 0.2163 | 0.3241 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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