---
library_name: transformers
license: apache-2.0
base_model: deepvk/RuModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: RuHalluBERT-base-v3
  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. -->

# RuHalluBERT-base-v3

This model is a fine-tuned version of [deepvk/RuModernBERT-base](https://huggingface.co/deepvk/RuModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7977
- F1 Macro: 0.6248
- F1 Class1: 0.6341
- F1 Class0: 0.6154
- Accuracy: 0.625
- Precision Macro: 0.6290
- Recall Macro: 0.6302

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- 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: cosine
- lr_scheduler_warmup_steps: 0.06
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Class1 | F1 Class0 | Accuracy | Precision Macro | Recall Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:--------:|:---------------:|:------------:|
| 13.9495       | 1.0   | 98   | 0.7467          | 0.4752   | 0.6256    | 0.3248    | 0.5183   | 0.6315          | 0.5669       |
| 11.2511       | 2.0   | 196  | 0.6250          | 0.6699   | 0.6860    | 0.6538    | 0.6707   | 0.6968          | 0.6897       |
| 9.3975        | 3.0   | 294  | 0.6134          | 0.6450   | 0.5758    | 0.7143    | 0.6585   | 0.6513          | 0.6439       |
| 8.1226        | 4.0   | 392  | 0.6403          | 0.6089   | 0.5373    | 0.6804    | 0.6220   | 0.6124          | 0.6084       |
| 7.3214        | 5.0   | 490  | 0.6810          | 0.7291   | 0.7027    | 0.7556    | 0.7317   | 0.7285          | 0.7318       |
| 4.5838        | 6.0   | 588  | 0.7438          | 0.7066   | 0.6207    | 0.7925    | 0.7317   | 0.7529          | 0.7051       |
| 2.3476        | 7.0   | 686  | 1.3592          | 0.6559   | 0.5593    | 0.7524    | 0.6829   | 0.6887          | 0.6571       |
| 0.8999        | 8.0   | 784  | 1.5965          | 0.6723   | 0.5984    | 0.7463    | 0.6890   | 0.6865          | 0.6708       |


### Framework versions

- Transformers 5.8.1
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2