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
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Base model
zhihan1996/DNABERT-2-117M