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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: 0.3879
- Accuracy: 0.8612
- Precision: 0.9154
- Recall: 0.8240
- F1: 0.8673

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4958        | 0.46  | 500  | 0.4749          | 0.7831   | 0.7303    | 0.9606 | 0.8298 |
| 0.3928        | 0.93  | 1000 | 0.4086          | 0.8207   | 0.7717    | 0.9574 | 0.8546 |
| 0.3319        | 1.39  | 1500 | 0.3467          | 0.8635   | 0.8664    | 0.8891 | 0.8776 |
| 0.3036        | 1.85  | 2000 | 0.3176          | 0.8702   | 0.8717    | 0.8960 | 0.8836 |
| 0.2383        | 2.31  | 2500 | 0.3403          | 0.8707   | 0.8901    | 0.8728 | 0.8814 |
| 0.2189        | 2.78  | 3000 | 0.3879          | 0.8612   | 0.9154    | 0.8240 | 0.8673 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3

{"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: 0.3879
* Accuracy: 0.8612
* Precision: 0.9154
* Recall: 0.8240
* F1: 0.8673


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 2.0.0+cu118
* Tokenizers 0.13.3



### 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 2.0.0+cu118
* Tokenizers 0.13.3
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 2.0.0+cu118
* Tokenizers 0.13.3
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 2.0.0+cu118
* Tokenizers 0.13.3