Administration_RuRoberta_test
This model is a fine-tuned version of sberbank-ai/ruRoberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3205
- Accuracy: 0.3316
- Top 2 Accuracy: 0.4452
- Top 3 Accuracy: 0.5217
- Roc Auc: 0.9245
- F1: 0.2788
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 12
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Top 2 Accuracy | Top 3 Accuracy | Roc Auc | F1 |
---|---|---|---|---|---|---|---|---|
4.9101 | 1.0 | 262 | 4.6292 | 0.0816 | 0.1301 | 0.1773 | 0.7633 | 0.0566 |
4.4492 | 2.0 | 524 | 3.8332 | 0.2564 | 0.3737 | 0.4528 | 0.8992 | 0.2009 |
3.9241 | 3.0 | 786 | 3.4448 | 0.3163 | 0.4222 | 0.5089 | 0.9194 | 0.2619 |
3.0492 | 4.0 | 1048 | 3.3205 | 0.3316 | 0.4452 | 0.5217 | 0.9245 | 0.2788 |
Framework versions
- Transformers 4.54.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
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Model tree for Goshective/Administration_RuRoberta_test
Base model
ai-forever/ruRoberta-large