---
base_model: DeepPavlov/xlm-roberta-large-en-ru-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: books_text_class_roBERTa_ru_base_iliabel
  results: []
---

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

This model is a fine-tuned version of [DeepPavlov/xlm-roberta-large-en-ru-mnli](https://huggingface.co/DeepPavlov/xlm-roberta-large-en-ru-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2345
- Accuracy: 0.9723
- F1-score: 0.9721
- Mcc: 0.9620

## 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: 1e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1-score | Mcc    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------:|
| 0.4345        | 1.0   | 1516  | 0.3400          | 0.9190   | 0.9035   | 0.8902 |
| 0.2621        | 2.0   | 3032  | 0.2285          | 0.9563   | 0.9557   | 0.9404 |
| 0.2166        | 3.0   | 4548  | 0.2311          | 0.9661   | 0.9634   | 0.9536 |
| 0.1465        | 4.0   | 6064  | 0.2608          | 0.9606   | 0.9591   | 0.9464 |
| 0.0841        | 5.0   | 7580  | 0.3028          | 0.9581   | 0.9578   | 0.9430 |
| 0.0736        | 6.0   | 9096  | 0.2167          | 0.9735   | 0.9734   | 0.9638 |
| 0.0263        | 7.0   | 10612 | 0.2355          | 0.9738   | 0.9735   | 0.9642 |
| 0.0294        | 8.0   | 12128 | 0.2305          | 0.9711   | 0.9707   | 0.9604 |
| 0.0079        | 9.0   | 13644 | 0.2317          | 0.9726   | 0.9724   | 0.9625 |
| 0.0051        | 10.0  | 15160 | 0.2345          | 0.9723   | 0.9721   | 0.9620 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0