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my_awesome_wnut_model
bjubert/my_awesome_wnut_model
my_awesome_wnut_model is a token classification model from bjubert. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 7, 2022
- Updated
- Dec 10, 2022
- SHA
- 3f6c63cc
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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. -->
my_awesome_wnut_model
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0968
- eval_overall_precision: 0.7090
- eval_overall_recall: 0.7537
- eval_overall_f1: 0.7306
- eval_overall_accuracy: 0.9731
- eval_HumanProd_f1: 0.3733
- eval_LOC_f1: 0.7596
- eval_ORG_f1: 0.5874
- eval_PER_f1: 0.7607
- eval_runtime: 123.6596
- eval_samples_per_second: 19.804
- eval_steps_per_second: 1.245
- epoch: 2.0
- step: 1226
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: 2
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cpu
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Dec 7, 2022
- Updated
- Dec 10, 2022