---
base_model: mor40/BulBERT-ner-bsnlp
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BulBERT-ner-bsnlp
  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. -->

# BulBERT-ner-bsnlp

This model is a fine-tuned version of [mor40/BulBERT-ner-bsnlp](https://huggingface.co/mor40/BulBERT-ner-bsnlp) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1443
- Precision: 0.7728
- Recall: 0.8862
- F1: 0.8257
- Accuracy: 0.9726

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 91   | 0.1395          | 0.7736    | 0.8690 | 0.8185 | 0.9717   |
| No log        | 2.0   | 182  | 0.1386          | 0.7466    | 0.8849 | 0.8099 | 0.9705   |
| No log        | 3.0   | 273  | 0.1408          | 0.7695    | 0.8782 | 0.8203 | 0.9726   |
| No log        | 4.0   | 364  | 0.1426          | 0.7680    | 0.8851 | 0.8224 | 0.9721   |
| No log        | 5.0   | 455  | 0.1443          | 0.7728    | 0.8862 | 0.8257 | 0.9726   |


### Framework versions

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