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bert-to-distilbert-NER
kushaljoseph/bert-to-distilbert-NER
bert-to-distilbert-NER is a token classification model from kushaljoseph. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- May 14, 2022
- Updated
- May 16, 2022
- SHA
- c65c2bd8
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Datasets
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. -->
bert-to-distilbert-NER
This model is a fine-tuned version of dslim/bert-base-NER on the conll2003 dataset. It achieves the following results on the evaluation set:
- eval_loss: 5.9063
- eval_precision: 0.0120
- eval_recall: 0.0069
- eval_f1: 0.0088
- eval_accuracy: 0.7600
- eval_runtime: 8.6309
- eval_samples_per_second: 376.671
- eval_steps_per_second: 3.012
- epoch: 1.0
- step: 110
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: 0.00023888106906613202
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.19.1
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- May 14, 2022
- Updated
- May 16, 2022