
<!-- 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. -->

# rutoxicity-classification

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the [Russian Language Toxic Comments](https://www.kaggle.com/datasets/blackmoon/russian-language-toxic-comments) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2747
- Acc: 0.9255

## 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: 0.0001
- 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: 6

### Training results



### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "rutoxicity-classification", "results": []}]}
transformers pytorch tensorboard bert generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #generated_from_trainer #endpoints_compatible #region-us 




# rutoxicity-classification

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the Russian Language Toxic Comments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2747
- Acc: 0.9255

## 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: 0.0001
- 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: 6

### Training results



### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

# rutoxicity-classification

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the Russian Language Toxic Comments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2747
- Acc: 0.9255 ## 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: 0.0001
- 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: 6 ### Training results ### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #generated_from_trainer #endpoints_compatible #region-us 
 # rutoxicity-classification

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the Russian Language Toxic Comments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2747
- Acc: 0.9255 ## 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: 0.0001
- 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: 6 ### Training results ### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #generated_from_trainer #endpoints_compatible #region-us 
# rutoxicity-classification

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the Russian Language Toxic Comments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2747
- Acc: 0.9255## 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: 0.0001
- 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: 6### Training results### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1