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# DNADebertaK6_Fruitfly

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7137

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 600001
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step   | Validation Loss |
|:-------------:|:------:|:------:|:---------------:|
| 4.5584        | 5.36   | 20000  | 1.9795          |
| 1.9682        | 10.73  | 40000  | 1.8618          |
| 1.8692        | 16.09  | 60000  | 1.8273          |
| 1.8339        | 21.45  | 80000  | 1.8076          |
| 1.8208        | 26.82  | 100000 | 1.8073          |
| 1.8105        | 32.18  | 120000 | 1.7925          |
| 1.8022        | 37.54  | 140000 | 1.7909          |
| 1.7955        | 42.91  | 160000 | 1.7836          |
| 1.7907        | 48.27  | 180000 | 1.7769          |
| 1.7849        | 53.63  | 200000 | 1.7755          |
| 1.7805        | 59.0   | 220000 | 1.7677          |
| 1.7769        | 64.36  | 240000 | 1.7690          |
| 1.7723        | 69.72  | 260000 | 1.7614          |
| 1.7689        | 75.09  | 280000 | 1.7586          |
| 1.7646        | 80.45  | 300000 | 1.7523          |
| 1.7607        | 85.81  | 320000 | 1.7484          |
| 1.7572        | 91.18  | 340000 | 1.7458          |
| 1.754         | 96.54  | 360000 | 1.7460          |
| 1.7498        | 101.9  | 380000 | 1.7326          |
| 1.7463        | 107.27 | 400000 | 1.7377          |
| 1.7438        | 112.63 | 420000 | 1.7318          |
| 1.7406        | 117.99 | 440000 | 1.7342          |
| 1.7383        | 123.36 | 460000 | 1.7339          |
| 1.7348        | 128.72 | 480000 | 1.7244          |
| 1.7324        | 134.08 | 500000 | 1.7236          |
| 1.7289        | 139.45 | 520000 | 1.7155          |
| 1.7268        | 144.81 | 540000 | 1.7254          |
| 1.725         | 150.17 | 560000 | 1.7191          |
| 1.7221        | 155.54 | 580000 | 1.7147          |
| 1.7209        | 160.9  | 600000 | 1.7137          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "DNADebertaK6_Fruitfly", "results": []}]}
transformers pytorch deberta fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

DNADebertaK6\_Fruitfly
======================


This model is a fine-tuned version of [](URL on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7137


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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 600001
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 600001
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #deberta #fill-mask #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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 600001
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #deberta #fill-mask #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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 600001
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0
* Datasets 2.2.2
* Tokenizers 0.12.1