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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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