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In2Lab_WFU_DETECH_ate_span_biobert_v1
ajtamayoh/In2Lab_WFU_DETECH_ate_span_biobert_v1
In2Lab_WFU_DETECH_ate_span_biobert_v1 is a machine learning model from ajtamayoh. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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Updated Feb 1, 2026
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Feb 1, 2026
- Updated
- Feb 1, 2026
- SHA
- 0a4716dd
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. -->
In2Lab_WFU_DETECH_ate_span_biobert_v1
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1151
- Precision: 0.7944
- Recall: 0.8041
- F1: 0.7992
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: 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: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 61 | 0.1674 | 0.7136 | 0.6143 | 0.6602 |
| No log | 2.0 | 122 | 0.1358 | 0.7411 | 0.7674 | 0.7540 |
| No log | 3.0 | 183 | 0.1245 | 0.7599 | 0.8028 | 0.7808 |
| No log | 4.0 | 244 | 0.1162 | 0.7852 | 0.7927 | 0.7889 |
| No log | 5.0 | 305 | 0.1140 | 0.7996 | 0.7976 | 0.7986 |
| No log | 6.0 | 366 | 0.1133 | 0.7943 | 0.8002 | 0.7972 |
| No log | 7.0 | 427 | 0.1151 | 0.7944 | 0.8041 | 0.7992 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Created
- Feb 1, 2026
- Updated
- Feb 1, 2026