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3adapter_ronbackbone_content
ttqdunggg/3adapter_ronbackbone_content
3adapter_ronbackbone_content is a machine learning model from ttqdunggg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as agpl-3.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- agpl-3.0
- Model type
- roberta
- Access
- Public
- Created
- Nov 13, 2025
- Updated
- Nov 13, 2025
- SHA
- 7648f0d5
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. -->
3adapter_ronbackbone_content
This model is a fine-tuned version of RonTon05/model_content_V2_test on the None dataset. It achieves the following results on the evaluation set:
- Acc Content: 0.9872
- F1 Content: 0.9852
- Loss: 0.0130
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Acc Content | F1 Content | Validation Loss |
|---|---|---|---|---|---|
| 0.0553 | 1.0 | 529 | 0.9872 | 0.9852 | 0.0150 |
| 0.018 | 2.0 | 1058 | 0.9872 | 0.9852 | 0.0132 |
| 0.0172 | 3.0 | 1587 | 0.9872 | 0.9852 | 0.0130 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
- Library
- transformers
- Type
- roberta
- License
- agpl-3.0
- Created
- Nov 13, 2025
- Updated
- Nov 13, 2025