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albert-large-v2-finetuned-abbDet-finetuned-ner-Custom
jaggernaut007/albert-large-v2-finetuned-abbDet-finetuned-ner-Custom
albert-large-v2-finetuned-abbDet-finetuned-ner-Custom is a token classification model from jaggernaut007. 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
- albert
- Access
- Public
- Created
- Apr 18, 2024
- Updated
- Apr 18, 2024
- SHA
- 7bd02747
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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. -->
albert-large-v2-finetuned-abbDet-finetuned-ner-Custom
This model is a fine-tuned version of surrey-nlp/albert-large-v2-finetuned-abbDet on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1315
- Precision: 0.9768
- Recall: 0.9733
- F1: 0.9750
- Accuracy: 0.9731
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1
- Task
- Token Classification
- Library
- transformers
- Type
- albert
- License
- apache-2.0
- Created
- Apr 18, 2024
- Updated
- Apr 18, 2024