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arxiv_scibert_classifier
GogiGigantic/arxiv_scibert_classifier
arxiv_scibert_classifier is a machine learning model from GogiGigantic. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- bert
- Access
- Public
- Created
- Apr 6, 2026
- Updated
- Apr 6, 2026
- SHA
- 15a5b6fc
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. -->
arxiv_scibert_classifier
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6849
- Accuracy: 0.8301
- F1 Macro: 0.8300
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.4732 | 1.0 | 3750 | 0.5591 | 0.8233 | 0.8235 |
| 0.3428 | 2.0 | 7500 | 0.5882 | 0.8225 | 0.8231 |
| 0.1935 | 3.0 | 11250 | 0.6849 | 0.8301 | 0.8300 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.19.1
- Type
- bert
- Created
- Apr 6, 2026
- Updated
- Apr 6, 2026