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bert-base-cased-ner-jnlpba-strong-labelled
yachty66/bert-base-cased-ner-jnlpba-strong-labelled
bert-base-cased-ner-jnlpba-strong-labelled is a token classification model from yachty66. 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
- Jan 11, 2023
- Updated
- Jan 11, 2023
- SHA
- 6fee2f01
Try a prompt
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-base-cased-ner-jnlpba-strong-labelled
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.7948
- eval_accuracy: 0.1970
- eval_runtime: 49.3802
- eval_samples_per_second: 156.217
- eval_steps_per_second: 9.781
- step: 0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 11, 2023
- Updated
- Jan 11, 2023