---
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rubert-base-cased-1-third
  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-base-cased-1-third

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2935
- Accuracy: 0.919

## 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: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6641        | 1.0   | 1500  | 0.3723          | 0.9029   |
| 0.285         | 2.0   | 3000  | 0.3000          | 0.9154   |
| 0.1981        | 3.0   | 4500  | 0.2935          | 0.919    |
| 0.1488        | 4.0   | 6000  | 0.3073          | 0.9194   |
| 0.1139        | 5.0   | 7500  | 0.3401          | 0.9177   |
| 0.0902        | 6.0   | 9000  | 0.3662          | 0.9166   |
| 0.077         | 7.0   | 10500 | 0.3955          | 0.9175   |
| 0.0633        | 8.0   | 12000 | 0.4064          | 0.916    |
| 0.0548        | 9.0   | 13500 | 0.4286          | 0.9173   |
| 0.0487        | 10.0  | 15000 | 0.4429          | 0.916    |
| 0.0405        | 11.0  | 16500 | 0.4777          | 0.9195   |
| 0.0367        | 12.0  | 18000 | 0.4836          | 0.9202   |
| 0.0314        | 13.0  | 19500 | 0.4854          | 0.9194   |
| 0.0271        | 14.0  | 21000 | 0.5018          | 0.9175   |
| 0.023         | 15.0  | 22500 | 0.5123          | 0.9191   |


### Framework versions

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