---
tags:
- generated_from_trainer
model-index:
- name: genome-bert
  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. -->

# genome-bert

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4267

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 400
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5187        | 0.65  | 1000  | 0.6013          |
| 0.4429        | 1.31  | 2000  | 0.5585          |
| 0.3791        | 1.96  | 3000  | 0.5298          |
| 0.3316        | 2.62  | 4000  | 0.5153          |
| 0.2991        | 3.27  | 5000  | 0.5025          |
| 0.3066        | 3.93  | 6000  | 0.4808          |
| 0.2795        | 4.58  | 7000  | 0.4675          |
| 0.2599        | 5.24  | 8000  | 0.4594          |
| 0.2432        | 5.89  | 9000  | 0.4460          |
| 0.2282        | 6.54  | 10000 | 0.4431          |
| 0.2167        | 7.2   | 11000 | 0.4381          |
| 0.2075        | 7.85  | 12000 | 0.4291          |
| 0.2013        | 8.51  | 13000 | 0.4307          |
| 0.1977        | 9.16  | 14000 | 0.4266          |
| 0.1951        | 9.82  | 15000 | 0.4267          |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2