---
base_model: s-nlp/russian_toxicity_classifier
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tg_comments_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tg_comments_model

This model is a fine-tuned version of [s-nlp/russian_toxicity_classifier](https://huggingface.co/s-nlp/russian_toxicity_classifier) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0519
- Precision: 0.9762
- Recall: 0.9856
- F1: 0.9809
- Accuracy: 0.9817

## 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-05
- train_batch_size: 64
- 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: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.075         | 0.2239 | 300  | 0.0591          | 0.9833    | 0.9731 | 0.9781 | 0.9793   |
| 0.0627        | 0.4478 | 600  | 0.0567          | 0.9749    | 0.9843 | 0.9796 | 0.9805   |
| 0.0612        | 0.6716 | 900  | 0.0537          | 0.9795    | 0.9821 | 0.9808 | 0.9817   |
| 0.0633        | 0.8955 | 1200 | 0.0519          | 0.9762    | 0.9856 | 0.9809 | 0.9817   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1