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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: 0.6698
- Precision: 0.7042
- Recall: 0.6698
- F1: 0.6640
- Loss: 0.7715
## 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 | 9 | 0.3820 | 0.1459 | 0.3820 | 0.2112 | 1.1479 |
| No log | 2.0 | 18 | 0.3820 | 0.1459 | 0.3820 | 0.2112 | 1.4862 |
| No log | 3.0 | 27 | 0.5385 | 0.2900 | 0.5385 | 0.3770 | 1.0168 |
| No log | 4.0 | 36 | 0.3820 | 0.1459 | 0.3820 | 0.2112 | 1.0134 |
| No log | 5.0 | 45 | 0.4551 | 0.6492 | 0.4551 | 0.3461 | 0.9242 |
| No log | 6.0 | 54 | 0.6217 | 0.6269 | 0.6217 | 0.5716 | 0.7808 |
| No log | 7.0 | 63 | 0.6183 | 0.6601 | 0.6183 | 0.5446 | 0.7970 |
| No log | 8.0 | 72 | 0.4519 | 0.6933 | 0.4519 | 0.3345 | 1.0565 |
| No log | 9.0 | 81 | 0.7000 | 0.6985 | 0.7000 | 0.6842 | 0.7125 |
| No log | 10.0 | 90 | 0.6480 | 0.6978 | 0.6480 | 0.6395 | 0.7874 |
| No log | 11.0 | 99 | 0.6226 | 0.7064 | 0.6226 | 0.6062 | 0.8571 |
| No log | 12.0 | 108 | 0.5364 | 0.7104 | 0.5364 | 0.4812 | 1.1975 |
| No log | 13.0 | 117 | 0.7423 | 0.7327 | 0.7423 | 0.7336 | 0.6509 |
| No log | 14.0 | 126 | 0.7372 | 0.7275 | 0.7372 | 0.7306 | 0.6489 |
| No log | 15.0 | 135 | 0.5954 | 0.7039 | 0.5954 | 0.5712 | 0.9821 |
| No log | 16.0 | 144 | 0.7372 | 0.7317 | 0.7372 | 0.7258 | 0.6768 |
| No log | 17.0 | 153 | 0.6457 | 0.7049 | 0.6457 | 0.6355 | 0.8276 |
| No log | 17.8235 | 160 | 0.6698 | 0.7042 | 0.6698 | 0.6640 | 0.7715 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0
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