rubert_level2
This model is a fine-tuned version of eternalGenius/rubert_level2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1661
- F1 Micro: 0.7178
- F1 Macro: 0.7076
- F1 Weighted: 0.7118
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- 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_steps: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 0.1082 | 1.0 | 97 | 0.1827 | 0.6862 | 0.6628 | 0.6653 |
| 0.0939 | 2.0 | 194 | 0.1743 | 0.7165 | 0.7000 | 0.7067 |
| 0.0861 | 3.0 | 291 | 0.1737 | 0.7198 | 0.7049 | 0.7055 |
| 0.0796 | 4.0 | 388 | 0.1735 | 0.7160 | 0.7074 | 0.7095 |
| 0.0771 | 5.0 | 485 | 0.1699 | 0.7089 | 0.6921 | 0.6923 |
| 0.0668 | 6.0 | 582 | 0.1661 | 0.7178 | 0.7076 | 0.7118 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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