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framework_test_single_model
iTroned/framework_test_single_model
framework_test_single_model 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. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Mar 27, 2025
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Mar 27, 2025
- Updated
- Mar 27, 2025
- SHA
- b74aba33
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. -->
framework_test_single_model
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2083
- Accuracy Offensive: 0.9441
- F1 Offensive: 0.9425
- Accuracy Targeted: 0.9441
- F1 Targeted: 0.9173
- Accuracy Stance: 0.9086
- F1 Stance: 0.8748
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Offensive | F1 Offensive | Accuracy Targeted | F1 Targeted | Accuracy Stance | F1 Stance |
|---|---|---|---|---|---|---|---|---|---|
| 0.2565 | 1.0 | 1490 | 0.2272 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9101 | 0.8824 |
| 0.2099 | 2.0 | 2980 | 0.2182 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9056 | 0.8720 |
| 0.1946 | 3.0 | 4470 | 0.2155 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9033 | 0.8710 |
| 0.1898 | 4.0 | 5960 | 0.2145 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9086 | 0.8735 |
| 0.1911 | 5.0 | 7450 | 0.2206 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9079 | 0.8717 |
| 0.1867 | 6.0 | 8940 | 0.2131 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9101 | 0.8768 |
| 0.1851 | 7.0 | 10430 | 0.2101 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9094 | 0.8764 |
| 0.1798 | 8.0 | 11920 | 0.2100 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9094 | 0.8754 |
| 0.1768 | 9.0 | 13410 | 0.2063 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9086 | 0.8735 |
| 0.1715 | 10.0 | 14900 | 0.2017 | 0.9441 | 0.9425 | 0.9441 | 0.9173 | 0.9094 | 0.8752 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- transformers
- License
- apache-2.0
- Created
- Mar 27, 2025
- Updated
- Mar 27, 2025