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HarmAug-Guard-tuned
gnurt2041/HarmAug-Guard-tuned
HarmAug-Guard-tuned is a text classification model from gnurt2041. Use it when you need a label for a piece of text. 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
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Oct 25, 2024
- Updated
- Oct 25, 2024
- SHA
- 0f86d89d
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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. -->
results
This model is a fine-tuned version of hbseong/HarmAug-Guard on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1008
- Accuracy: 0.9667
- Precision: 0.9667
- Recall: 0.9667
- F1: 0.9667
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4652 | 0.9895 | 59 | 0.2876 | 0.9417 | 0.9445 | 0.9417 | 0.9414 |
| 0.003 | 1.9958 | 119 | 0.1736 | 0.9667 | 0.9689 | 0.9667 | 0.9667 |
| 0.0027 | 2.9853 | 178 | 0.2779 | 0.95 | 0.9519 | 0.95 | 0.9499 |
| 0.1023 | 3.9916 | 238 | 0.3743 | 0.9333 | 0.9408 | 0.9333 | 0.9328 |
| 0.0015 | 4.9979 | 298 | 0.3164 | 0.9417 | 0.9417 | 0.9417 | 0.9416 |
| 0.0003 | 5.9874 | 357 | 0.2952 | 0.9583 | 0.9614 | 0.9583 | 0.9582 |
| 0.0002 | 6.9937 | 417 | 0.2069 | 0.9417 | 0.9426 | 0.9417 | 0.9416 |
| 0.0001 | 8.0 | 477 | 0.1738 | 0.9583 | 0.9584 | 0.9583 | 0.9583 |
| 0.0001 | 8.9895 | 536 | 0.1008 | 0.9667 | 0.9667 | 0.9667 | 0.9667 |
| 0.0001 | 9.8952 | 590 | 0.1016 | 0.9667 | 0.9667 | 0.9667 | 0.9667 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Oct 25, 2024
- Updated
- Oct 25, 2024