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ner-bio-annotated-3
urbija/ner-bio-annotated-3
ner-bio-annotated-3 is a token classification model from urbija. 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
- bert
- Access
- Public
- Created
- Aug 18, 2023
- Updated
- Aug 28, 2023
- SHA
- fe1a8d1b
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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. -->
ner-bio-annotated-3
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1888
- Precision: 0.7117
- Recall: 0.7350
- F1: 0.7232
- Accuracy: 0.9461
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 67 | 0.2365 | 0.6361 | 0.6498 | 0.6429 | 0.9329 |
| No log | 2.0 | 134 | 0.2017 | 0.6667 | 0.7079 | 0.6866 | 0.9445 |
| No log | 3.0 | 201 | 0.1888 | 0.7117 | 0.7350 | 0.7232 | 0.9461 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Aug 18, 2023
- Updated
- Aug 28, 2023