---
base_model: mor40/BulBERT-chitanka-model
tags:
- generated_from_trainer
datasets:
- bgglue
metrics:
- accuracy
model-index:
- name: BulBERT-xnli-2epochs
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: bgglue
      type: bgglue
      config: xnlibg
      split: validation
      args: xnlibg
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7016064257028113
---

<!-- 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-xnli-2epochs

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: 0.7013
- Accuracy: 0.7016

## 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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7543        | 1.0   | 8182  | 0.7510          | 0.6731   |
| 0.6804        | 2.0   | 16364 | 0.7013          | 0.7016   |


### Framework versions

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