Downloads · 30 days
6
16% of all-time downloads
distilbert-german-finetuned-ner-v2
MissAvery/distilbert-german-finetuned-ner-v2
distilbert-german-finetuned-ner-v2 is a token classification model from MissAvery. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
37
Public
Parameters
66.8M
267 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors267 MB · 100%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 8, 2025
- Updated
- Sep 18, 2025
- SHA
- 2aaa5832
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
distilbert-german-finetuned-ner-v2
This model is a fine-tuned version of distilbert-base-german-cased on a custom dataset. It achieves the following results on the evaluation set:
- Loss: 0.0016
- Precision: 0.9985
- Recall: 0.9982
- F1: 0.9983
- Accuracy: 0.9995
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.041 | 1.0 | 1000 | 0.0077 | 0.9919 | 0.9934 | 0.9926 | 0.9980 |
| 0.0068 | 2.0 | 2000 | 0.0041 | 0.9969 | 0.9971 | 0.9970 | 0.9989 |
| 0.0032 | 3.0 | 3000 | 0.0016 | 0.9985 | 0.9982 | 0.9983 | 0.9995 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 8, 2025
- Updated
- Sep 18, 2025