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--- |
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license: apache-2.0 |
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base_model: jonatasgrosman/wav2vec2-large-xlsr-53-russian |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr-53-ru-snr10-commonvoice_train3000_val200 |
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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: common_voice_11_0 |
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type: common_voice_11_0 |
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config: ru |
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split: test[0:200] |
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args: ru |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5075114304376225 |
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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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# wav2vec2-large-xlsr-53-ru-snr10-commonvoice_train3000_val200 |
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-russian](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-russian) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3736 |
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- Wer: 0.5075 |
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- Cer: 0.2395 |
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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: 16 |
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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: 30 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 0.9298 | 0.96 | 180 | 1.0829 | 0.6153 | 0.2984 | |
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| 0.6185 | 1.91 | 360 | 1.1071 | 0.5924 | 0.2899 | |
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| 0.5395 | 2.87 | 540 | 1.0219 | 0.5558 | 0.2604 | |
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| 0.464 | 3.83 | 720 | 1.0042 | 0.5363 | 0.2564 | |
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| 0.4346 | 4.79 | 900 | 0.9817 | 0.5323 | 0.2403 | |
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| 0.4025 | 5.74 | 1080 | 1.0918 | 0.5558 | 0.2549 | |
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| 0.358 | 6.7 | 1260 | 1.0987 | 0.5336 | 0.2437 | |
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| 0.3466 | 7.66 | 1440 | 1.0802 | 0.5349 | 0.2437 | |
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| 0.3215 | 8.62 | 1620 | 1.1377 | 0.5467 | 0.2588 | |
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| 0.3247 | 9.57 | 1800 | 1.0324 | 0.5153 | 0.2350 | |
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| 0.287 | 10.53 | 1980 | 1.1466 | 0.5565 | 0.2603 | |
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| 0.2716 | 11.49 | 2160 | 1.2634 | 0.5532 | 0.2536 | |
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| 0.2555 | 12.45 | 2340 | 1.1859 | 0.5160 | 0.2318 | |
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| 0.2454 | 13.4 | 2520 | 1.1147 | 0.5186 | 0.2278 | |
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| 0.2299 | 14.36 | 2700 | 1.1287 | 0.5167 | 0.2282 | |
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| 0.2269 | 15.32 | 2880 | 1.2123 | 0.5042 | 0.2275 | |
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| 0.2132 | 16.28 | 3060 | 1.1219 | 0.5082 | 0.2297 | |
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| 0.1965 | 17.23 | 3240 | 1.2263 | 0.5167 | 0.2345 | |
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| 0.1943 | 18.19 | 3420 | 1.2679 | 0.5284 | 0.2353 | |
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| 0.1867 | 19.15 | 3600 | 1.2097 | 0.5186 | 0.2422 | |
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| 0.1851 | 20.11 | 3780 | 1.3118 | 0.5147 | 0.2330 | |
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| 0.1709 | 21.06 | 3960 | 1.1834 | 0.5193 | 0.2374 | |
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| 0.1757 | 22.02 | 4140 | 1.3010 | 0.5036 | 0.2272 | |
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| 0.1661 | 22.98 | 4320 | 1.2384 | 0.5075 | 0.2313 | |
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| 0.1607 | 23.94 | 4500 | 1.3642 | 0.5219 | 0.2421 | |
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| 0.1611 | 24.89 | 4680 | 1.3055 | 0.5108 | 0.2363 | |
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| 0.1567 | 25.85 | 4860 | 1.3666 | 0.5140 | 0.2383 | |
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| 0.1469 | 26.81 | 5040 | 1.3888 | 0.5101 | 0.2367 | |
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| 0.1432 | 27.77 | 5220 | 1.3478 | 0.5206 | 0.2333 | |
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| 0.1479 | 28.72 | 5400 | 1.3297 | 0.4918 | 0.2291 | |
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| 0.144 | 29.68 | 5580 | 1.3736 | 0.5075 | 0.2395 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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