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dnabert_genomic
vojtam/dnabert_genomic
dnabert_genomic is a text classification model from vojtam. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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117M
469 MB on disk
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Nov 18, 2024
- Updated
- Nov 18, 2024
- SHA
- 5e1fcc5a
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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. -->
dnabert_genomic
This model is a fine-tuned version of zhihan1996/DNABERT-2-117M on Genomic_Benchmarks_human_enhancers_cohn. It achieves the following results on the evaluation set:
- Loss: 0.4892
- Accuracy: 0.7601
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: 1.8621576331491283e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch 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 |
|---|---|---|---|---|
| No log | 1.0 | 261 | 0.4974 | 0.7563 |
| 0.5156 | 2.0 | 522 | 0.4951 | 0.7515 |
| 0.5156 | 3.0 | 783 | 0.4892 | 0.7601 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.2.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 18, 2024
- Updated
- Nov 18, 2024