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2_task_ronbackbone
ttqdunggg/2_task_ronbackbone
2_task_ronbackbone 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 23, 2025
- Updated
- Nov 24, 2025
- SHA
- 17d7cfae
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. -->
2_task_ronbackbone
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:
- Loss: 0.9458
- F1 Task1: 0.9899
- F1 Task2: 0.7693
- Acc Task1: 0.9943
- Acc Task2: 0.7594
- F1: 0.8796
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
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Task1 | F1 Task2 | Acc Task1 | Acc Task2 | F1 |
|---|---|---|---|---|---|---|---|---|
| 1.6713 | 1.0 | 275 | 1.2787 | 0.9891 | 0.2942 | 0.9939 | 0.5770 | 0.6417 |
| 1.0858 | 2.0 | 550 | 0.9996 | 0.9878 | 0.5125 | 0.9932 | 0.6705 | 0.7502 |
| 0.8193 | 3.0 | 825 | 0.8985 | 0.9883 | 0.6905 | 0.9934 | 0.7264 | 0.8394 |
| 0.6378 | 4.0 | 1100 | 0.8489 | 0.9882 | 0.7155 | 0.9934 | 0.7396 | 0.8518 |
| 0.5047 | 5.0 | 1375 | 0.8162 | 0.9883 | 0.7595 | 0.9934 | 0.7582 | 0.8739 |
| 0.3987 | 6.0 | 1650 | 0.8093 | 0.9887 | 0.7604 | 0.9936 | 0.7605 | 0.8745 |
| 0.3203 | 7.0 | 1925 | 0.8862 | 0.9907 | 0.7591 | 0.9948 | 0.7535 | 0.8749 |
| 0.2643 | 8.0 | 2200 | 0.9012 | 0.9899 | 0.7689 | 0.9943 | 0.7646 | 0.8794 |
| 0.2207 | 9.0 | 2475 | 0.9342 | 0.9899 | 0.7761 | 0.9943 | 0.7612 | 0.8830 |
| 0.1959 | 10.0 | 2750 | 0.9458 | 0.9899 | 0.7693 | 0.9943 | 0.7594 | 0.8796 |
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 23, 2025
- Updated
- Nov 24, 2025