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---
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
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