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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: russian-BERT |
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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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# russian-BERT |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0126 |
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- Accuracy: 0.8813 |
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- Precision: 0.8813 |
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- Recall: 0.8813 |
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- Micro-avg-recall: 0.8813 |
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- Micro-avg-precision: 0.8813 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:| |
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| 0.0795 | 1.0 | 750 | 0.8896 | 0.8637 | 0.8665 | 0.8637 | 0.8637 | 0.8637 | |
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| 0.073 | 2.0 | 1500 | 0.8294 | 0.8633 | 0.8640 | 0.8633 | 0.8633 | 0.8633 | |
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| 0.0001 | 3.0 | 2250 | 0.9873 | 0.8757 | 0.8779 | 0.8757 | 0.8757 | 0.8757 | |
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| 0.0432 | 4.0 | 3000 | 0.9801 | 0.8813 | 0.8817 | 0.8813 | 0.8813 | 0.8813 | |
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| 0.0002 | 5.0 | 3750 | 1.0126 | 0.8813 | 0.8813 | 0.8813 | 0.8813 | 0.8813 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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