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ner-fine-tune
cehongw/ner-fine-tune
ner-fine-tune is a token classification model from cehongw. 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
- roberta
- Access
- Public
- Created
- Oct 24, 2023
- Updated
- Oct 27, 2023
- SHA
- 35291fe4
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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. -->
ner-fine-tune
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4071
- eval_precision: 0.28
- eval_recall: 0.2972
- eval_f1: 0.2883
- eval_accuracy: 0.9461
- eval_runtime: 4.9447
- eval_samples_per_second: 43.886
- eval_steps_per_second: 5.663
- epoch: 37.0
- step: 3885
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: 1e-05
- 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
- num_epochs: 50
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Oct 24, 2023
- Updated
- Oct 27, 2023