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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-base-russian-demo-kaggle |
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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-base-russian-demo-kaggle |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.9997 |
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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: 12 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 24 |
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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: 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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.0102 | 1.03 | 500 | inf | 0.9997 | |
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| 0.0068 | 2.06 | 1000 | inf | 0.9997 | |
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| 0.0 | 3.09 | 1500 | inf | 0.9997 | |
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| 0.0313 | 4.12 | 2000 | inf | 0.9997 | |
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| 0.0 | 5.15 | 2500 | inf | 0.9997 | |
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| 0.0052 | 6.19 | 3000 | inf | 0.9997 | |
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| 0.0287 | 7.22 | 3500 | inf | 0.9997 | |
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| 0.0 | 8.25 | 4000 | inf | 0.9997 | |
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| 0.01 | 9.28 | 4500 | inf | 0.9997 | |
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| 0.0 | 10.31 | 5000 | inf | 0.9997 | |
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| 0.3919 | 11.34 | 5500 | inf | 0.9997 | |
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| 0.0 | 12.37 | 6000 | inf | 0.9997 | |
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| 0.0 | 13.4 | 6500 | inf | 0.9997 | |
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| 0.0 | 14.43 | 7000 | inf | 0.9997 | |
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| 0.6422 | 15.46 | 7500 | inf | 0.9997 | |
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| 0.0 | 16.49 | 8000 | inf | 0.9997 | |
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| 0.0 | 17.53 | 8500 | inf | 0.9997 | |
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| 0.0 | 18.56 | 9000 | inf | 0.9997 | |
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| 0.0 | 19.59 | 9500 | inf | 0.9997 | |
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| 0.0 | 20.62 | 10000 | inf | 0.9997 | |
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| 0.0427 | 21.65 | 10500 | inf | 0.9997 | |
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| 0.0 | 22.68 | 11000 | inf | 0.9997 | |
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| 0.0 | 23.71 | 11500 | inf | 0.9997 | |
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| 0.0 | 24.74 | 12000 | inf | 0.9997 | |
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| 0.0091 | 25.77 | 12500 | inf | 0.9997 | |
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| 0.1243 | 26.8 | 13000 | inf | 0.9997 | |
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| 0.0 | 27.83 | 13500 | inf | 0.9997 | |
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| 0.0 | 28.87 | 14000 | inf | 0.9997 | |
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| 0.0 | 29.9 | 14500 | inf | 0.9997 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.9.1 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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