distilbert-base-multilingual-cased-danish-probelmatic-labeller
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the data-is-better-together/fineweb-c dataset. It achieves the following results on the evaluation set:
- Loss: 0.1384
- F1: 0.9562
- Precision: 0.9717
- Recall: 0.9412
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.2528 | 2.0576 | 500 | 0.2187 | 0.8585 | 0.9220 | 0.8032 |
| 0.1169 | 4.1152 | 1000 | 0.1652 | 0.9193 | 0.9449 | 0.8951 |
| 0.0536 | 6.1728 | 1500 | 0.1470 | 0.9443 | 0.9667 | 0.9229 |
| 0.023 | 8.2305 | 2000 | 0.1384 | 0.9562 | 0.9717 | 0.9412 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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