---
library_name: transformers
license: mit
base_model: seara/rubert-tiny2-russian-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: rubert-tiny2-sentiment-tuned
  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-sentiment-tuned

This model is a fine-tuned version of [seara/rubert-tiny2-russian-sentiment](https://huggingface.co/seara/rubert-tiny2-russian-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2380
- Accuracy: 0.9248
- F1: 0.9274

## 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: 3e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.4865        | 0.1926 | 500  | 0.3455          | 0.8853   | 0.9123 |
| 0.3198        | 0.3852 | 1000 | 0.2753          | 0.9127   | 0.9218 |
| 0.2655        | 0.5778 | 1500 | 0.2513          | 0.9217   | 0.9260 |
| 0.2506        | 0.7704 | 2000 | 0.2415          | 0.9240   | 0.9270 |
| 0.2511        | 0.9630 | 2500 | 0.2380          | 0.9248   | 0.9274 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0