---
library_name: transformers
license: mit
base_model: sergeyzh/rubert-tiny-turbo
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: results3
  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. -->

# results3

This model is a fine-tuned version of [sergeyzh/rubert-tiny-turbo](https://huggingface.co/sergeyzh/rubert-tiny-turbo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2500
- Accuracy: 0.9661
- Recall: 0.6584
- Precision: 0.7737
- F1: 0.7114
- Roc Auc: 0.9492

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Recall | Precision | F1     | Roc Auc |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.2936        | 0.9988 | 633  | 0.2757          | 0.9337   | 0.6646 | 0.4842    | 0.5602 | 0.9290  |
| 0.2674        | 1.9992 | 1267 | 0.2230          | 0.9487   | 0.7391 | 0.5749    | 0.6467 | 0.9465  |
| 0.1575        | 2.9996 | 1901 | 0.2500          | 0.9661   | 0.6584 | 0.7737    | 0.7114 | 0.9492  |
| 0.0435        | 4.0    | 2535 | 0.2891          | 0.9613   | 0.7516 | 0.6760    | 0.7118 | 0.9476  |
| 0.0021        | 4.9941 | 3165 | 0.3548          | 0.9629   | 0.6770 | 0.7219    | 0.6987 | 0.9460  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0