---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ajders/ddisco
metrics:
- accuracy
base_model: NbAiLab/nb-bert-base
model-index:
- name: ddisco_classifier
  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. -->

# da-discourse-coherence-base

This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co./NbAiLab/nb-bert-base) on the [DDisco](https://huggingface.co./datasets/ajders/ddisco) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7487
- Accuracy: 0.6915

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 703
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3422        | 0.4   | 5    | 1.0166          | 0.5721   |
| 0.9645        | 0.8   | 10   | 0.8966          | 0.5721   |
| 0.9854        | 1.24  | 15   | 0.8499          | 0.5721   |
| 0.8628        | 1.64  | 20   | 0.8379          | 0.6517   |
| 0.9046        | 2.08  | 25   | 0.8228          | 0.5721   |
| 0.8361        | 2.48  | 30   | 0.7980          | 0.5821   |
| 0.8158        | 2.88  | 35   | 0.8095          | 0.5821   |
| 0.8689        | 3.32  | 40   | 0.7989          | 0.6169   |
| 0.8125        | 3.72  | 45   | 0.7730          | 0.6965   |
| 0.843         | 4.16  | 50   | 0.7566          | 0.6418   |
| 0.7421        | 4.56  | 55   | 0.7840          | 0.6517   |
| 0.7949        | 4.96  | 60   | 0.7531          | 0.6915   |
| 0.828         | 5.4   | 65   | 0.7464          | 0.6816   |
| 0.7438        | 5.8   | 70   | 0.7487          | 0.6915   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0a0+d0d6b1f
- Datasets 2.9.0
- Tokenizers 0.13.2

### Contributor

[ajders](https://github.com/AJDERS)