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library_name: transformers
license: apache-2.0
base_model: deepvk/RuModernBERT-small
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: rumodernbert_ner_ft_small
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rumodernbert_ner_ft_small
This model is a fine-tuned version of [deepvk/RuModernBERT-small](https://huggingface.co/deepvk/RuModernBERT-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2842
- F1: 0.8257
- Precision: 0.8080
- Recall: 0.8443
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 1.3906 | 0.32 | 200 | 0.6057 | 0.4393 | 0.3840 | 0.5132 |
| 0.8110 | 0.64 | 400 | 0.3561 | 0.6269 | 0.5835 | 0.6774 |
| 0.6350 | 0.96 | 600 | 0.3008 | 0.7213 | 0.6812 | 0.7665 |
| 0.4992 | 1.28 | 800 | 0.2633 | 0.7803 | 0.7699 | 0.7909 |
| 0.3823 | 1.6 | 1000 | 0.2300 | 0.8084 | 0.7936 | 0.8238 |
| 0.3995 | 1.92 | 1200 | 0.2162 | 0.8009 | 0.7918 | 0.8102 |
| 0.2860 | 2.24 | 1400 | 0.2195 | 0.8109 | 0.7988 | 0.8234 |
| 0.2833 | 2.56 | 1600 | 0.2065 | 0.8140 | 0.7955 | 0.8335 |
| 0.2660 | 2.88 | 1800 | 0.2374 | 0.8145 | 0.8020 | 0.8274 |
| 0.1466 | 3.2 | 2000 | 0.2693 | 0.8079 | 0.7838 | 0.8335 |
| 0.1809 | 3.52 | 2200 | 0.2504 | 0.8299 | 0.8210 | 0.8391 |
| 0.1685 | 3.84 | 2400 | 0.2267 | 0.8315 | 0.8134 | 0.8503 |
| 0.0860 | 4.16 | 2600 | 0.2938 | 0.8273 | 0.8106 | 0.8447 |
| 0.0884 | 4.48 | 2800 | 0.2980 | 0.8183 | 0.7959 | 0.8419 |
| 0.1116 | 4.8 | 3000 | 0.2842 | 0.8257 | 0.8080 | 0.8443 |
### Framework versions
- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.7.0
- Tokenizers 0.22.2
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