---
base_model: mor40/BulBERT-chitanka-model
tags:
- generated_from_trainer
datasets:
- bgglue
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BulBERT-ner-udep-5epochs
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: bgglue
      type: bgglue
      config: udep
      split: validation
      args: udep
    metrics:
    - name: Precision
      type: precision
      value: 0.975273754856941
    - name: Recall
      type: recall
      value: 0.975273754856941
    - name: F1
      type: f1
      value: 0.975273754856941
    - name: Accuracy
      type: accuracy
      value: 0.9777743637015415
---

<!-- 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-ner-udep-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: 0.1089
- Precision: 0.9753
- Recall: 0.9753
- F1: 0.9753
- Accuracy: 0.9778

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1134        | 1.0   | 1114 | 0.0996          | 0.9674    | 0.9673 | 0.9673 | 0.9721   |
| 0.0578        | 2.0   | 2228 | 0.0933          | 0.9728    | 0.9722 | 0.9725 | 0.9760   |
| 0.0321        | 3.0   | 3342 | 0.0993          | 0.9739    | 0.9746 | 0.9743 | 0.9769   |
| 0.0178        | 4.0   | 4456 | 0.1054          | 0.9746    | 0.9750 | 0.9748 | 0.9776   |
| 0.0096        | 5.0   | 5570 | 0.1089          | 0.9753    | 0.9753 | 0.9753 | 0.9778   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1