---
tags:
- generated_from_trainer
datasets:
- danish_legal_pile
metrics:
- accuracy
model-index:
- name: danish-legal-longformer-base-mlm
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: danish_legal_pile
      type: danish_legal_pile
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8285689003181987
---

<!-- 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. -->

# danish-legal-longformer-base-mlm

This model is a fine-tuned version of [data/plms/danish-legal-longformer-base](https://huggingface.co/data/plms/danish-legal-longformer-base) on the danish_legal_pile dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7374
- Accuracy: 0.8286

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 64000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7425        | 14.69 | 32000 | 0.7502          | 0.8259   |
| 0.7257        | 29.37 | 64000 | 0.7368          | 0.8287   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.12.0+cu113
- Datasets 2.0.0
- Tokenizers 0.12.1