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bert-base-uncased-finetuned-TF-mottos
cafierom/bert-base-uncased-finetuned-TF-mottos
bert-base-uncased-finetuned-TF-mottos is a text classification model from cafierom. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
A model to predict if a text string is an Autobot or Decepticon motto!
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Feb 6, 2025
- Updated
- Feb 7, 2025
- SHA
- f06c16d2
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Base models
Model card
From the Hugging Face model README
A model to predict if a text string is an Autobot or Decepticon motto!
bert-base-uncased-finetuned-TF-mottos
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: 0.6088
- Accuracy: 0.7241
- F1: 0.7241
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: 32
- eval_batch_size: 32
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7065 | 1.0 | 16 | 0.6716 | 0.6897 | 0.6855 |
| 0.6407 | 2.0 | 32 | 0.6404 | 0.6552 | 0.6446 |
| 0.5087 | 3.0 | 48 | 0.6088 | 0.7241 | 0.7241 |
| 0.3035 | 4.0 | 64 | 0.7323 | 0.6552 | 0.6636 |
| 0.1443 | 5.0 | 80 | 0.9169 | 0.5862 | 0.5952 |
| 0.0619 | 6.0 | 96 | 1.3918 | 0.5517 | 0.5517 |
| 0.0494 | 7.0 | 112 | 1.5762 | 0.6207 | 0.6207 |
| 0.0154 | 8.0 | 128 | 1.4311 | 0.6552 | 0.6636 |
| 0.0052 | 9.0 | 144 | 1.8390 | 0.5862 | 0.5901 |
| 0.0031 | 10.0 | 160 | 1.8705 | 0.6207 | 0.6270 |
| 0.0021 | 11.0 | 176 | 1.9632 | 0.6207 | 0.6270 |
| 0.0018 | 12.0 | 192 | 2.0319 | 0.6207 | 0.6270 |
| 0.0115 | 13.0 | 208 | 2.0895 | 0.6207 | 0.6270 |
| 0.0014 | 14.0 | 224 | 2.2048 | 0.5862 | 0.5901 |
| 0.0012 | 15.0 | 240 | 2.2127 | 0.6207 | 0.6270 |
| 0.0011 | 16.0 | 256 | 2.2382 | 0.6207 | 0.6270 |
| 0.0011 | 17.0 | 272 | 2.2513 | 0.6207 | 0.6270 |
| 0.001 | 18.0 | 288 | 2.2649 | 0.6207 | 0.6270 |
| 0.001 | 19.0 | 304 | 2.2752 | 0.6207 | 0.6270 |
| 0.001 | 20.0 | 320 | 2.2845 | 0.5862 | 0.5901 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 6, 2025
- Updated
- Feb 7, 2025