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--- |
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library_name: transformers |
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base_model: sberbank-ai/ruRoberta-large |
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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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- f1 |
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model-index: |
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- name: Administration_RuRoberta_test |
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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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# Administration_RuRoberta_test |
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This model is a fine-tuned version of [sberbank-ai/ruRoberta-large](https://huggingface.co/sberbank-ai/ruRoberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3205 |
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- Accuracy: 0.3316 |
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- Top 2 Accuracy: 0.4452 |
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- Top 3 Accuracy: 0.5217 |
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- Roc Auc: 0.9245 |
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- F1: 0.2788 |
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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: 12 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 4 |
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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 | Accuracy | Top 2 Accuracy | Top 3 Accuracy | Roc Auc | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|:--------------:|:-------:|:------:| |
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| 4.9101 | 1.0 | 262 | 4.6292 | 0.0816 | 0.1301 | 0.1773 | 0.7633 | 0.0566 | |
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| 4.4492 | 2.0 | 524 | 3.8332 | 0.2564 | 0.3737 | 0.4528 | 0.8992 | 0.2009 | |
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| 3.9241 | 3.0 | 786 | 3.4448 | 0.3163 | 0.4222 | 0.5089 | 0.9194 | 0.2619 | |
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| 3.0492 | 4.0 | 1048 | 3.3205 | 0.3316 | 0.4452 | 0.5217 | 0.9245 | 0.2788 | |
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### Framework versions |
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- Transformers 4.54.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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