---
license: mit
tags:
- generated_from_trainer
base_model: r1char9/rubert-base-cased-russian-sentiment
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ru_sentiment_classification_model
  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. -->

# ru_sentiment_classification_model

This model is a fine-tuned version of [r1char9/rubert-base-cased-russian-sentiment](https://huggingface.co./r1char9/rubert-base-cased-russian-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6368
- Accuracy: 0.8875
- Precision: 0.8990
- Recall: 0.8875
- F1: 0.8867

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8144        | 1.0   | 1854 | 0.7593          | 0.6630   | 0.6739    | 0.6630 | 0.6549 |
| 0.6734        | 2.0   | 3708 | 0.5688          | 0.7917   | 0.7933    | 0.7917 | 0.7899 |
| 0.5025        | 3.0   | 5562 | 0.5219          | 0.8238   | 0.8423    | 0.8238 | 0.8229 |
| 0.354         | 4.0   | 7416 | 0.4655          | 0.8912   | 0.8960    | 0.8912 | 0.8914 |
| 0.229         | 5.0   | 9270 | 0.6368          | 0.8875   | 0.8990    | 0.8875 | 0.8867 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1