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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2 russian |
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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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# wav2vec2-russian |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2972 |
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- Wer: 0.4920 |
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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: 1e-05 |
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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: 1000 |
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- num_epochs: 6 |
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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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| 0.6885 | 0.25 | 500 | 1.2398 | 0.4926 | |
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| 0.6499 | 0.5 | 1000 | 1.2338 | 0.4957 | |
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| 0.6446 | 0.74 | 1500 | 1.2716 | 0.4975 | |
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| 0.6966 | 0.99 | 2000 | 1.5439 | 0.4942 | |
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| 0.7188 | 1.24 | 2500 | 1.4889 | 0.4960 | |
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| 0.7116 | 1.49 | 3000 | 1.0075 | 0.4921 | |
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| 0.7178 | 1.73 | 3500 | 1.3123 | 0.4984 | |
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| 0.7034 | 1.98 | 4000 | 1.1037 | 0.4919 | |
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| 0.7116 | 2.23 | 4500 | 0.9947 | 0.4942 | |
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| 0.7203 | 2.48 | 5000 | 1.1547 | 0.4940 | |
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| 0.72 | 2.73 | 5500 | 1.1245 | 0.4960 | |
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| 0.6921 | 2.97 | 6000 | 1.0844 | 0.4947 | |
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| 0.702 | 3.22 | 6500 | 1.1999 | 0.4931 | |
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| 0.6965 | 3.47 | 7000 | 1.2106 | 0.4906 | |
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| 0.6928 | 3.72 | 7500 | 1.1275 | 0.4939 | |
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| 0.6973 | 3.96 | 8000 | 1.1953 | 0.4922 | |
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| 0.7065 | 4.21 | 8500 | 1.2046 | 0.4931 | |
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| 0.6921 | 4.46 | 9000 | 1.2052 | 0.4926 | |
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| 0.6977 | 4.71 | 9500 | 1.2806 | 0.4922 | |
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| 0.688 | 4.96 | 10000 | 1.3327 | 0.4926 | |
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| 0.7003 | 5.2 | 10500 | 1.3518 | 0.4930 | |
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| 0.6981 | 5.45 | 11000 | 1.3295 | 0.4936 | |
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| 0.6913 | 5.7 | 11500 | 1.3065 | 0.4928 | |
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| 0.6822 | 5.95 | 12000 | 1.2972 | 0.4920 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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