---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rubert-tiny2-1-4
  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. -->

# rubert-tiny2-1-4

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: 0.3882
- Accuracy: 0.9001

## 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: 1e-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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.9597        | 1.0   | 1500  | 1.1052          | 0.7613   |
| 0.9583        | 2.0   | 3000  | 0.8140          | 0.8157   |
| 0.7343        | 3.0   | 4500  | 0.6514          | 0.8502   |
| 0.6076        | 4.0   | 6000  | 0.5656          | 0.867    |
| 0.5257        | 5.0   | 7500  | 0.5115          | 0.8771   |
| 0.4694        | 6.0   | 9000  | 0.4748          | 0.8826   |
| 0.4296        | 7.0   | 10500 | 0.4477          | 0.8885   |
| 0.4006        | 8.0   | 12000 | 0.4295          | 0.8938   |
| 0.3753        | 9.0   | 13500 | 0.4159          | 0.896    |
| 0.358         | 10.0  | 15000 | 0.4066          | 0.8979   |
| 0.3417        | 11.0  | 16500 | 0.3994          | 0.8992   |
| 0.3296        | 12.0  | 18000 | 0.3943          | 0.8993   |
| 0.3203        | 13.0  | 19500 | 0.3914          | 0.8993   |
| 0.3158        | 14.0  | 21000 | 0.3889          | 0.9001   |
| 0.3126        | 15.0  | 22500 | 0.3882          | 0.9001   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0