---
base_model: mor40/BulBERT-chitanka-model
tags:
- generated_from_trainer
datasets:
- bgglue
metrics:
- accuracy
model-index:
- name: BulBERT-fakenews-5epochs
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: bgglue
      type: bgglue
      config: fakenews
      split: validation
      args: fakenews
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9049773755656109
---

<!-- 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. -->

# BulBERT-fakenews-5epochs

This model is a fine-tuned version of [mor40/BulBERT-chitanka-model](https://huggingface.co/mor40/BulBERT-chitanka-model) on the bgglue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3487
- Accuracy: 0.9050

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 84   | 0.4732          | 0.7511   |
| No log        | 2.0   | 168  | 0.3922          | 0.8552   |
| No log        | 3.0   | 252  | 0.3230          | 0.8778   |
| No log        | 4.0   | 336  | 0.3518          | 0.8959   |
| No log        | 5.0   | 420  | 0.3487          | 0.9050   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1