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# output

This model is a fine-tuned version of [zhihan1996/DNA_bert_6](https://huggingface.co/zhihan1996/DNA_bert_6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3966
- Accuracy: 0.8492
- Precision: 0.8807
- Recall: 0.8283
- F1: 0.8537

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4859        | 0.41  | 500  | 0.4180          | 0.8001   | 0.8552    | 0.7506 | 0.7995 |
| 0.3937        | 0.81  | 1000 | 0.4044          | 0.8217   | 0.8871    | 0.7612 | 0.8193 |
| 0.3426        | 1.22  | 1500 | 0.3740          | 0.8340   | 0.8765    | 0.8    | 0.8365 |
| 0.3068        | 1.63  | 2000 | 0.3839          | 0.8398   | 0.8808    | 0.8077 | 0.8426 |
| 0.2757        | 2.04  | 2500 | 0.4260          | 0.8386   | 0.8181    | 0.8950 | 0.8548 |
| 0.2211        | 2.44  | 3000 | 0.3966          | 0.8492   | 0.8807    | 0.8283 | 0.8537 |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "output", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

output
======


This model is a fine-tuned version of zhihan1996/DNA\_bert\_6 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3966
* Accuracy: 0.8492
* Precision: 0.8807
* Recall: 0.8283
* F1: 0.8537


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Tokenizers 0.13.2