---
license: apache-2.0
base_model: ctheodoris/Geneformer
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Geneformer_ft_BioS2_1kbpHG19_DHSs_H3K27AC
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Geneformer_ft_BioS2_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: 0.6514
- F1 Score: 0.6398
- Precision: 0.6615
- Recall: 0.6195
- Accuracy: 0.6273
- Auc: 0.6654
- Prc: 0.6684

## 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    |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
| 0.6959        | 0.0841 | 500  | 0.6846          | 0.6785   | 0.5633    | 0.8530 | 0.5681   | 0.5765 | 0.5859 |
| 0.6879        | 0.1682 | 1000 | 0.6892          | 0.3661   | 0.6392    | 0.2565 | 0.5254   | 0.5823 | 0.6044 |
| 0.6913        | 0.2523 | 1500 | 0.6919          | 0.2450   | 0.6413    | 0.1514 | 0.5013   | 0.5921 | 0.6000 |
| 0.6854        | 0.3364 | 2000 | 0.6722          | 0.6928   | 0.5659    | 0.8930 | 0.5769   | 0.6111 | 0.6274 |
| 0.6774        | 0.4205 | 2500 | 0.6637          | 0.6896   | 0.5917    | 0.8263 | 0.6026   | 0.6321 | 0.6402 |
| 0.6667        | 0.5045 | 3000 | 0.6546          | 0.6895   | 0.6083    | 0.7957 | 0.6171   | 0.6509 | 0.6561 |
| 0.6791        | 0.5886 | 3500 | 0.6514          | 0.6398   | 0.6615    | 0.6195 | 0.6273   | 0.6654 | 0.6684 |


### Framework versions

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