---
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ruBertTiny_attr_name_addv3
  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. -->

# ruBertTiny_attr_name_addv3

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: 0.2154
- Accuracy: 0.9188

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step   | Validation Loss | Accuracy |
|:-------------:|:------:|:------:|:---------------:|:--------:|
| 0.5515        | 0.2739 | 10000  | 0.4502          | 0.7949   |
| 0.49          | 0.5478 | 20000  | 0.3874          | 0.8205   |
| 0.4632        | 0.8217 | 30000  | 0.3556          | 0.8376   |
| 0.4367        | 1.0956 | 40000  | 0.3381          | 0.8419   |
| 0.4122        | 1.3695 | 50000  | 0.3138          | 0.8590   |
| 0.3989        | 1.6434 | 60000  | 0.2787          | 0.8932   |
| 0.389         | 1.9173 | 70000  | 0.2741          | 0.8846   |
| 0.3669        | 2.1912 | 80000  | 0.2523          | 0.9017   |
| 0.3566        | 2.4651 | 90000  | 0.2459          | 0.8932   |
| 0.3502        | 2.7391 | 100000 | 0.2343          | 0.9017   |
| 0.3458        | 3.0130 | 110000 | 0.2248          | 0.9145   |
| 0.3281        | 3.2869 | 120000 | 0.2203          | 0.9145   |
| 0.3255        | 3.5608 | 130000 | 0.2162          | 0.9145   |
| 0.3234        | 3.8347 | 140000 | 0.2176          | 0.9274   |
| 0.3174        | 4.1086 | 150000 | 0.2147          | 0.9188   |
| 0.3126        | 4.3825 | 160000 | 0.2138          | 0.9145   |
| 0.3127        | 4.6564 | 170000 | 0.2155          | 0.9188   |
| 0.3126        | 4.9303 | 180000 | 0.2154          | 0.9188   |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.0.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1