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---
license: apache-2.0
base_model: ctheodoris/Geneformer
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Geneformer_ft_BioS45_1kbpHG19_DHSs_H3K27AC
  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. -->

# Geneformer_ft_BioS45_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of [ctheodoris/Geneformer](https://huggingface.co/ctheodoris/Geneformer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6631
- F1 Score: 0.5409
- Precision: 0.6586
- Recall: 0.4589
- Accuracy: 0.5936
- Auc: 0.6567
- Prc: 0.6689

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc    | Prc    |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
| 0.6972        | 0.2103 | 500  | 0.6987          | 0.0      | 0.0       | 0.0    | 0.4783   | 0.5304 | 0.5397 |
| 0.6932        | 0.4207 | 1000 | 0.6899          | 0.6877   | 0.5307    | 0.9766 | 0.5372   | 0.5631 | 0.5685 |
| 0.6931        | 0.6310 | 1500 | 0.6869          | 0.4327   | 0.6091    | 0.3355 | 0.5410   | 0.5889 | 0.5992 |
| 0.6827        | 0.8414 | 2000 | 0.6669          | 0.6767   | 0.5763    | 0.8194 | 0.5915   | 0.6392 | 0.6453 |
| 0.6667        | 1.0517 | 2500 | 0.6631          | 0.5409   | 0.6586    | 0.4589 | 0.5936   | 0.6567 | 0.6689 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.0