---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-multilingual-cased-IDMGSP-danish
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-cased-IDMGSP-danish

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9588
- Accuracy: {'accuracy': 0.8393768817908103}
- F1: {'f1': 0.8521508615495843}

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
| 0.4777        | 1.0   | 480  | 0.3597          | {'accuracy': 0.8594056813719073} | {'f1': 0.8543926247288504} |
| 0.3642        | 2.0   | 960  | 0.5526          | {'accuracy': 0.8147663306715539} | {'f1': 0.8337836250440502} |
| 0.3087        | 3.0   | 1440 | 0.3296          | {'accuracy': 0.8677837413273989} | {'f1': 0.8711077080142932} |
| 0.1919        | 4.0   | 1920 | 0.4540          | {'accuracy': 0.8287733996596414} | {'f1': 0.8453169347209082} |
| 0.1592        | 5.0   | 2400 | 0.3791          | {'accuracy': 0.8701400706898809} | {'f1': 0.8696794534944824} |
| 0.1324        | 6.0   | 2880 | 0.5328          | {'accuracy': 0.8294279355936641} | {'f1': 0.8443435670768128} |
| 0.1271        | 7.0   | 3360 | 0.7168          | {'accuracy': 0.8440895405157743} | {'f1': 0.8535955746773203} |
| 0.0227        | 8.0   | 3840 | 0.8978          | {'accuracy': 0.8253698128027229} | {'f1': 0.8424285376801323} |
| 0.0019        | 9.0   | 4320 | 0.8289          | {'accuracy': 0.8507658070428067} | {'f1': 0.8595367175948743} |
| 0.0046        | 10.0  | 4800 | 0.9588          | {'accuracy': 0.8393768817908103} | {'f1': 0.8521508615495843} |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1