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bact_roberta_base_essentiality_Network
sms112/bact_roberta_base_essentiality_Network
bact_roberta_base_essentiality_Network is a text classification model from sms112. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Feb 15, 2026
- Updated
- Feb 15, 2026
- SHA
- 6e7e36c9
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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. -->
bact_roberta_base_essentiality_Network
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4141
- Accuracy: 0.8310
- Precision: 0.8400
- Recall: 0.8178
- F1: 0.8287
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: 3e-05
- train_batch_size: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 72 | 0.6554 | 0.6588 | 0.6020 | 0.9368 | 0.7330 |
| No log | 2.0 | 144 | 0.4637 | 0.7838 | 0.7997 | 0.7573 | 0.7779 |
| No log | 3.0 | 216 | 0.4541 | 0.7931 | 0.7745 | 0.8271 | 0.7999 |
| No log | 4.0 | 288 | 0.4764 | 0.7982 | 0.7630 | 0.8652 | 0.8109 |
| No log | 5.0 | 360 | 0.4254 | 0.8129 | 0.8037 | 0.8280 | 0.8157 |
| No log | 6.0 | 432 | 0.4175 | 0.8224 | 0.8329 | 0.8066 | 0.8196 |
| 1.8208 | 7.0 | 504 | 0.4262 | 0.8259 | 0.8251 | 0.8271 | 0.8261 |
| 1.8208 | 8.0 | 576 | 0.4154 | 0.8296 | 0.8376 | 0.8178 | 0.8276 |
| 1.8208 | 9.0 | 648 | 0.4140 | 0.8310 | 0.8400 | 0.8178 | 0.8287 |
| 1.8208 | 10.0 | 720 | 0.4235 | 0.8254 | 0.8241 | 0.8275 | 0.8258 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Feb 15, 2026
- Updated
- Feb 15, 2026