metadata
library_name: transformers
license: apache-2.0
base_model: deepvk/RuModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: rumodernbert_ner_ft
results: []
rumodernbert_ner_ft
This model is a fine-tuned version of deepvk/RuModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2121
- F1: 0.8730
- Precision: 0.8596
- Recall: 0.8868
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.5866 | 0.32 | 200 | 0.2772 | 0.7188 | 0.6785 | 0.7640 |
| 0.4701 | 0.64 | 400 | 0.2204 | 0.7867 | 0.7535 | 0.8230 |
| 0.4275 | 0.96 | 600 | 0.1895 | 0.8191 | 0.7932 | 0.8467 |
| 0.3282 | 1.28 | 800 | 0.1970 | 0.8339 | 0.8155 | 0.8531 |
| 0.2545 | 1.6 | 1000 | 0.1765 | 0.8553 | 0.8427 | 0.8684 |
| 0.2703 | 1.92 | 1200 | 0.1528 | 0.8626 | 0.8512 | 0.8744 |
| 0.1658 | 2.24 | 1400 | 0.1862 | 0.8610 | 0.8476 | 0.8748 |
| 0.1571 | 2.56 | 1600 | 0.1882 | 0.8617 | 0.8464 | 0.8776 |
| 0.1604 | 2.88 | 1800 | 0.1715 | 0.8760 | 0.8638 | 0.8884 |
| 0.0633 | 3.2 | 2000 | 0.2327 | 0.8656 | 0.8443 | 0.8880 |
| 0.0925 | 3.52 | 2200 | 0.2032 | 0.8757 | 0.8641 | 0.8876 |
| 0.0730 | 3.84 | 2400 | 0.2121 | 0.8730 | 0.8596 | 0.8868 |
Framework versions
- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.7.0
- Tokenizers 0.22.2