---
base_model: ai-forever/ruBert-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-chn-classifier
  results: []
---

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

This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2343
- Accuracy: 0.9595
- Precision: 0.9595
- Recall: 0.9595
- F1: 0.9595

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2249        | 1.0   | 4381  | 0.1770          | 0.9513   | 0.9513    | 0.9513 | 0.9513 |
| 0.1078        | 2.0   | 8762  | 0.1951          | 0.9571   | 0.9571    | 0.9571 | 0.9571 |
| 0.0234        | 3.0   | 13143 | 0.2343          | 0.9595   | 0.9595    | 0.9595 | 0.9595 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1