---
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: results_synt_data
  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. -->

# results_synt_data

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1310
- Precision: 0.7870
- Recall: 0.8681
- F1: 0.8256
- Accuracy: 0.9644

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.061         | 1.0   | 2700  | 0.2892          | 0.4979    | 0.6620 | 0.5684 | 0.9082   |
| 0.0426        | 2.0   | 5400  | 0.1871          | 0.6795    | 0.7840 | 0.7280 | 0.9438   |
| 0.0321        | 3.0   | 8100  | 0.1526          | 0.7172    | 0.8293 | 0.7692 | 0.9519   |
| 0.0257        | 4.0   | 10800 | 0.1382          | 0.7414    | 0.8407 | 0.7880 | 0.9566   |
| 0.0211        | 5.0   | 13500 | 0.1359          | 0.7545    | 0.8477 | 0.7984 | 0.9587   |
| 0.0182        | 6.0   | 16200 | 0.1300          | 0.7738    | 0.8581 | 0.8138 | 0.9620   |
| 0.015         | 7.0   | 18900 | 0.1344          | 0.7811    | 0.8616 | 0.8194 | 0.9625   |
| 0.0135        | 8.0   | 21600 | 0.1309          | 0.7810    | 0.8681 | 0.8223 | 0.9628   |
| 0.0135        | 9.0   | 24300 | 0.1326          | 0.7881    | 0.8681 | 0.8261 | 0.9643   |
| 0.0121        | 10.0  | 27000 | 0.1310          | 0.7870    | 0.8681 | 0.8256 | 0.9644   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1