---
license: cc-by-4.0
base_model: NbAiLab/nb-bert-large
tags:
- generated_from_trainer
model-index:
- name: nb-bert-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-FGN

This model is a fine-tuned version of [NbAiLab/nb-bert-large](https://huggingface.co/NbAiLab/nb-bert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8455
- F1-score: 0.8640

## 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  | 0.4694          | 0.8310   |
| No log        | 2.0   | 240  | 0.4810          | 0.8225   |
| No log        | 3.0   | 360  | 0.3942          | 0.8528   |
| No log        | 4.0   | 480  | 0.7082          | 0.7709   |
| 0.4938        | 5.0   | 600  | 0.7041          | 0.8333   |
| 0.4938        | 6.0   | 720  | 0.6616          | 0.8528   |
| 0.4938        | 7.0   | 840  | 0.9447          | 0.8226   |
| 0.4938        | 8.0   | 960  | 0.8971          | 0.8464   |
| 0.2424        | 9.0   | 1080 | 0.9245          | 0.8348   |
| 0.2424        | 10.0  | 1200 | 0.8455          | 0.8640   |
| 0.2424        | 11.0  | 1320 | 0.8109          | 0.8571   |
| 0.2424        | 12.0  | 1440 | 1.0194          | 0.8566   |
| 0.1235        | 13.0  | 1560 | 0.9609          | 0.8533   |
| 0.1235        | 14.0  | 1680 | 1.0777          | 0.8435   |
| 0.1235        | 15.0  | 1800 | 1.1128          | 0.8450   |
| 0.1235        | 16.0  | 1920 | 1.0391          | 0.8582   |
| 0.0621        | 17.0  | 2040 | 1.1569          | 0.8507   |
| 0.0621        | 18.0  | 2160 | 1.1449          | 0.8492   |
| 0.0621        | 19.0  | 2280 | 1.1715          | 0.8492   |
| 0.0621        | 20.0  | 2400 | 1.1702          | 0.8564   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1