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bert-base-multilingual-uncased-fire-classification-silvanus
rollerhafeezh/bert-base-multilingual-uncased-fire-classification-silvanus
bert-base-multilingual-uncased-fire-classification-silvanus is a text classification model from rollerhafeezh. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jan 29, 2024
- Updated
- Jan 31, 2024
- SHA
- b3263a53
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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. -->
bert-base-multilingual-uncased-fire-classification-silvanus
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3995
- Accuracy: 0.9099
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 233 | 0.3059 | 0.8927 |
| No log | 2.0 | 466 | 0.3349 | 0.9013 |
| 0.3183 | 3.0 | 699 | 0.3995 | 0.9099 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 29, 2024
- Updated
- Jan 31, 2024