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ontology-complaint
scales-okn/ontology-complaint
ontology-complaint is a text classification model from scales-okn. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- deberta-v2
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 12, 2023
- SHA
- f80852e1
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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. -->
ontology-complaint
This model is a fine-tuned version of scales-okn/docket-language-model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0384
- Accuracy: 0.9955
- F1: 0.9944
- Precision: 0.9889
- Recall: 1.0
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0019 | 1.27 | 100 | 0.0552 | 0.9910 | 0.9889 | 0.9780 | 1.0 |
| 0.0007 | 2.53 | 200 | 0.0714 | 0.9910 | 0.9889 | 0.9780 | 1.0 |
| 0.0002 | 3.8 | 300 | 0.0384 | 0.9955 | 0.9944 | 0.9889 | 1.0 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- Created
- Mar 2, 2022
- Updated
- Jan 12, 2023