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optuna_test
iTroned/optuna_test
optuna_test is a machine learning model from iTroned. 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.
should probably proofread and complete it, then remove this comment. --
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Updated Apr 20, 2025
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Apr 19, 2025
- Updated
- Apr 20, 2025
- SHA
- 74155857
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. -->
optuna_test
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8628
- Accuracy Offensive: 0.7817
- F1 Macro Offensive: 0.7653
- F1 Weighted Offensive: 0.7845
- Accuracy Targeted: 0.7092
- F1 Macro Targeted: 0.4759
- F1 Weighted Targeted: 0.7040
- Accuracy Stance: 0.5208
- F1 Macro Stance: 0.2490
- F1 Weighted Stance: 0.5497
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: 1.8430176522412313e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Offensive | F1 Macro Offensive | F1 Weighted Offensive | Accuracy Targeted | F1 Macro Targeted | F1 Weighted Targeted | Accuracy Stance | F1 Macro Stance | F1 Weighted Stance |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.9547 | 1.0 | 662 | 0.8672 | 0.7836 | 0.7645 | 0.7852 | 0.7202 | 0.4818 | 0.7141 | 0.4966 | 0.2407 | 0.5316 |
| 0.8257 | 2.0 | 1324 | 0.8628 | 0.7817 | 0.7653 | 0.7845 | 0.7092 | 0.4759 | 0.7040 | 0.5208 | 0.2490 | 0.5497 |
| 0.7823 | 3.0 | 1986 | 0.9847 | 0.7764 | 0.7618 | 0.7800 | 0.7096 | 0.4749 | 0.7039 | 0.5340 | 0.2504 | 0.5581 |
| 0.6509 | 4.0 | 2648 | 1.1280 | 0.7779 | 0.7603 | 0.7804 | 0.7421 | 0.4923 | 0.7321 | 0.5819 | 0.2686 | 0.5885 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.0.1
- Tokenizers 0.21.1
- Library
- transformers
- Created
- Apr 19, 2025
- Updated
- Apr 20, 2025