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distilbert_bc2gm_corpus
deeptij2007/distilbert_bc2gm_corpus
distilbert_bc2gm_corpus is a token classification model from deeptij2007. 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. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Sep 30, 2025
- Updated
- Oct 1, 2025
- SHA
- a62da23c
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. -->
my_awesome_wnut_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0855
- Precision: 0.6957
- Recall: 0.7594
- F1: 0.7261
- Accuracy: 0.9687
Model description
NER model trained on spyysalo/bc2gm_corpus
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1964 | 1.0 | 782 | 0.0925 | 0.6539 | 0.7442 | 0.6961 | 0.9639 |
| 0.0737 | 2.0 | 1564 | 0.0855 | 0.6957 | 0.7594 | 0.7261 | 0.9687 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 30, 2025
- Updated
- Oct 1, 2025