---
base_model: mor40/BulBERT-chitanka-model
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BulBERT-ner-wikiann_3epochs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BulBERT-ner-wikiann_3epochs

This model is a fine-tuned version of [mor40/BulBERT-chitanka-model](https://huggingface.co/mor40/BulBERT-chitanka-model) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2315
- Precision: 0.7856
- Recall: 0.8456
- F1: 0.8145
- Accuracy: 0.9419

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2412        | 1.0   | 2030 | 0.2453          | 0.7370    | 0.8098 | 0.7716 | 0.9275   |
| 0.159         | 2.0   | 4060 | 0.2240          | 0.7746    | 0.8358 | 0.8040 | 0.9393   |
| 0.1014        | 3.0   | 6090 | 0.2315          | 0.7856    | 0.8456 | 0.8145 | 0.9419   |


### Framework versions

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