---
language:
- da
license: mit
model-index:
- name: contract-ner-model-da
  results:
  - task:
      type: token-classification
      name: Token Classification
widget:
- "Medarbejderen ansættes til 35.000,00 kr. om måneden og arbejdsstedet er Supergaden 21, 2000 Frederiksberg."
inference:
  parameters:
    aggregation_strategy: "first"
---

# contract-ner-model-da

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on a custom contracts dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0100
- Micro F1: 0.9074
- Micro F1 No Misc: 0.9074

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4356
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Micro F1 No Misc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|
| 1.1722        | 4.88  | 200  | 0.0612          | 0.0      | 0.0              |
| 0.0341        | 9.76  | 400  | 0.0209          | 0.0      | 0.0              |
| 0.0158        | 14.63 | 600  | 0.0109          | 0.7233   | 0.7233           |
| 0.0085        | 19.51 | 800  | 0.0097          | 0.7727   | 0.7727           |
| 0.0057        | 24.39 | 1000 | 0.0084          | 0.8319   | 0.8319           |
| 0.0041        | 29.27 | 1200 | 0.0085          | 0.8630   | 0.8630           |
| 0.0031        | 34.15 | 1400 | 0.0089          | 0.8261   | 0.8261           |
| 0.0023        | 39.02 | 1600 | 0.0066          | 0.8785   | 0.8785           |
| 0.0017        | 43.9  | 1800 | 0.0106          | 0.8164   | 0.8164           |
| 0.0012        | 48.78 | 2000 | 0.0092          | 0.8730   | 0.8730           |
| 0.0008        | 53.66 | 2200 | 0.0076          | 0.8868   | 0.8868           |
| 0.0007        | 58.54 | 2400 | 0.0075          | 0.9017   | 0.9017           |
| 0.0005        | 63.41 | 2600 | 0.0096          | 0.8806   | 0.8806           |
| 0.0004        | 68.29 | 2800 | 0.0094          | 0.8852   | 0.8852           |
| 0.0004        | 73.17 | 3000 | 0.0084          | 0.9126   | 0.9126           |
| 0.0003        | 78.05 | 3200 | 0.0083          | 0.8986   | 0.8986           |
| 0.0003        | 82.93 | 3400 | 0.0093          | 0.9144   | 0.9144           |
| 0.0003        | 87.8  | 3600 | 0.0088          | 0.9231   | 0.9231           |
| 0.0001        | 92.68 | 3800 | 0.0080          | 0.9280   | 0.9280           |
| 0.0002        | 97.56 | 4000 | 0.0100          | 0.9074   | 0.9074           |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3