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e2-disaster-classifier
hems-1-1/e2-disaster-classifier
e2-disaster-classifier is a text classification model from hems-1-1. 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
- distilbert
- Access
- Public
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026
- SHA
- ebf5ce17
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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. -->
e2-disaster-classifier
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4910
- Accuracy: 0.7798
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: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6540 | 0.4931 | 500 | 0.5356 | 0.7437 |
| 0.5912 | 0.9862 | 1000 | 0.5064 | 0.7683 |
| 0.5456 | 1.4793 | 1500 | 0.4970 | 0.7865 |
| 0.5039 | 1.9724 | 2000 | 0.4832 | 0.7685 |
| 0.4553 | 2.4655 | 2500 | 0.4954 | 0.7820 |
| 0.4558 | 2.9586 | 3000 | 0.4910 | 0.7798 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026