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---
library_name: transformers
base_model: zhihan1996/DNABERT-2-117M
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dnabert_genomic
results: []
---
<!-- 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](https://huggingface.co/zhihan1996/DNABERT-2-117M) on [Genomic_Benchmarks_human_enhancers_cohn](https://huggingface.co/datasets/katarinagresova/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
|