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bert-finetuned-requirements
andyuk/bert-finetuned-requirements
bert-finetuned-requirements is a token classification model from andyuk. 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 14, 2023
- Updated
- Jan 14, 2023
- SHA
- 360c38bc
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-finetuned-requirements
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5811
- Precision: 0.7722
- Recall: 0.6854
- F1: 0.7262
- Accuracy: 0.8297
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 15 | 0.8961 | 0.7234 | 0.3820 | 0.5 | 0.6865 |
| No log | 2.0 | 30 | 0.6572 | 0.7584 | 0.6348 | 0.6911 | 0.8054 |
| No log | 3.0 | 45 | 0.5811 | 0.7722 | 0.6854 | 0.7262 | 0.8297 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 14, 2023
- Updated
- Jan 14, 2023