---
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ruBertTiny_attr_name_addv2
  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_addv2

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: 0.3093
- Accuracy: 0.8889

## 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: 5e-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 |
|:-------------:|:------:|:------:|:---------------:|:--------:|
| 0.5285        | 0.2739 | 10000  | 0.4378          | 0.8120   |
| 0.463         | 0.5478 | 20000  | 0.4148          | 0.8077   |
| 0.4241        | 0.8217 | 30000  | 0.4169          | 0.8077   |
| 0.3883        | 1.0956 | 40000  | 0.3991          | 0.8248   |
| 0.3607        | 1.3695 | 50000  | 0.3772          | 0.8419   |
| 0.3496        | 1.6434 | 60000  | 0.3689          | 0.8333   |
| 0.3408        | 1.9173 | 70000  | 0.3249          | 0.8718   |
| 0.3127        | 2.1912 | 80000  | 0.3308          | 0.8803   |
| 0.2974        | 2.4651 | 90000  | 0.3100          | 0.8803   |
| 0.2961        | 2.7391 | 100000 | 0.3057          | 0.8974   |
| 0.2884        | 3.0130 | 110000 | 0.3024          | 0.8889   |
| 0.2594        | 3.2869 | 120000 | 0.3040          | 0.8846   |
| 0.2588        | 3.5608 | 130000 | 0.3169          | 0.8803   |
| 0.2581        | 3.8347 | 140000 | 0.2961          | 0.8974   |
| 0.2483        | 4.1086 | 150000 | 0.3061          | 0.8803   |
| 0.2375        | 4.3825 | 160000 | 0.3045          | 0.8846   |
| 0.2378        | 4.6564 | 170000 | 0.3091          | 0.8889   |
| 0.2367        | 4.9303 | 180000 | 0.3093          | 0.8889   |


### Framework versions

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