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my_text_model
zhang-zx25/my_text_model
my_text_model is a machine learning model from zhang-zx25. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026
- SHA
- 00630daa
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. -->
my_text_model
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4176
- Accuracy: 0.8279
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 134 | 0.4896 | 0.7639 |
| No log | 2.0 | 268 | 0.4176 | 0.8279 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.7.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Type
- bert
- License
- mit
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026