Administration_RuRoberta_new_loss
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: 3.6653
- Accuracy: 0.3202
- Top 2 Accuracy: 0.4426
- Top 3 Accuracy: 0.5179
- Roc Auc: 0.9061
- F1: 0.2676
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_FUSED 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 |
---|---|---|---|---|---|---|---|---|
4.9575 | 1.0 | 262 | 4.7123 | 0.0778 | 0.1339 | 0.1696 | 0.7271 | 0.0495 |
4.6051 | 2.0 | 524 | 4.0959 | 0.25 | 0.375 | 0.4515 | 0.8816 | 0.2047 |
4.1213 | 3.0 | 786 | 3.7706 | 0.3010 | 0.4286 | 0.5115 | 0.9014 | 0.2493 |
3.4723 | 4.0 | 1048 | 3.6653 | 0.3202 | 0.4426 | 0.5179 | 0.9061 | 0.2676 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Downloads last month
- 10
Model tree for Goshective/Administration_RuRoberta_new_loss
Base model
ai-forever/ruRoberta-large