---
license: cc-by-4.0
base_model: NbAiLab/nb-bert-base
tags:
- generated_from_trainer
model-index:
- name: nb-bert-base_FGN
  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. -->

# nb-bert-base_FGN

This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0904
- F1-score: 0.8074

## 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: 5e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 120  | 0.6228          | 0.7307   |
| No log        | 2.0   | 240  | 0.7442          | 0.7474   |
| No log        | 3.0   | 360  | 0.7118          | 0.7785   |
| No log        | 4.0   | 480  | 1.2081          | 0.7137   |
| 0.5388        | 5.0   | 600  | 1.1968          | 0.7628   |
| 0.5388        | 6.0   | 720  | 1.0904          | 0.8074   |
| 0.5388        | 7.0   | 840  | 1.2685          | 0.8007   |
| 0.5388        | 8.0   | 960  | 1.4070          | 0.7783   |
| 0.123         | 9.0   | 1080 | 1.6120          | 0.7608   |
| 0.123         | 10.0  | 1200 | 1.5899          | 0.7695   |
| 0.123         | 11.0  | 1320 | 1.4975          | 0.7705   |
| 0.123         | 12.0  | 1440 | 1.4624          | 0.7983   |
| 0.0475        | 13.0  | 1560 | 1.5148          | 0.7711   |
| 0.0475        | 14.0  | 1680 | 1.4680          | 0.7926   |
| 0.0475        | 15.0  | 1800 | 1.4216          | 0.8006   |
| 0.0475        | 16.0  | 1920 | 1.4962          | 0.8006   |
| 0.0201        | 17.0  | 2040 | 1.4150          | 0.7883   |
| 0.0201        | 18.0  | 2160 | 1.4259          | 0.7755   |
| 0.0201        | 19.0  | 2280 | 1.5040          | 0.7799   |
| 0.0201        | 20.0  | 2400 | 1.5045          | 0.7808   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1