---
library_name: transformers
license: cc-by-4.0
base_model: vesteinn/DanskBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: danskbert_indirect_speech
  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. -->

# danskbert_indirect_speech

This model is a fine-tuned version of [vesteinn/DanskBERT](https://huggingface.co/vesteinn/DanskBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.6570
- Precision: 0.6586
- Recall: 0.6570
- F1: 0.6525
- Loss: 0.8216

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
| No log        | 1.0   | 13   | 0.5457   | 0.5231    | 0.5457 | 0.4294 | 1.0285          |
| No log        | 2.0   | 26   | 0.4100   | 0.1876    | 0.4100 | 0.2461 | 1.0252          |
| No log        | 3.0   | 39   | 0.5023   | 0.6704    | 0.5023 | 0.4244 | 0.8830          |
| No log        | 4.0   | 52   | 0.4991   | 0.7051    | 0.4991 | 0.4072 | 1.2035          |
| No log        | 5.0   | 65   | 0.4291   | 0.7156    | 0.4291 | 0.2829 | 1.3921          |
| No log        | 6.0   | 78   | 0.5491   | 0.7090    | 0.5491 | 0.4926 | 0.9938          |
| No log        | 7.0   | 91   | 0.5763   | 0.7044    | 0.5763 | 0.5365 | 1.0815          |
| No log        | 8.0   | 104  | 0.6624   | 0.6520    | 0.6624 | 0.6503 | 0.7027          |
| No log        | 9.0   | 117  | 0.6374   | 0.6696    | 0.6374 | 0.6308 | 0.9327          |
| No log        | 10.0  | 130  | 0.6549   | 0.6680    | 0.6549 | 0.6484 | 0.7493          |
| No log        | 11.0  | 143  | 0.6552   | 0.6597    | 0.6552 | 0.6499 | 0.7772          |
| No log        | 12.0  | 156  | 0.6604   | 0.6500    | 0.6604 | 0.6536 | 0.7496          |
| No log        | 13.0  | 169  | 0.6556   | 0.6643    | 0.6556 | 0.6502 | 0.8145          |
| No log        | 14.0  | 182  | 0.6588   | 0.6591    | 0.6588 | 0.6536 | 0.7831          |
| No log        | 15.0  | 195  | 0.6622   | 0.6604    | 0.6622 | 0.6572 | 0.7797          |
| No log        | 16.0  | 208  | 0.6588   | 0.6661    | 0.6588 | 0.6532 | 0.8084          |
| No log        | 17.0  | 221  | 0.6624   | 0.6672    | 0.6624 | 0.6578 | 0.8129          |
| No log        | 18.0  | 234  | 0.6597   | 0.6617    | 0.6597 | 0.6550 | 0.8171          |
| No log        | 18.48 | 240  | 0.6570   | 0.6586    | 0.6570 | 0.6525 | 0.8216          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0