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# DNADebertaK6_Zebrafish

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: 1.4958

## 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 |
|:-------------:|:-----:|:------:|:---------------:|
| 4.1727        | 0.59  | 20000  | 1.8535          |
| 1.8381        | 1.18  | 40000  | 1.7512          |
| 1.7561        | 1.77  | 60000  | 1.7235          |
| 1.7281        | 2.36  | 80000  | 1.7019          |
| 1.7065        | 2.95  | 100000 | 1.6822          |
| 1.6876        | 3.54  | 120000 | 1.6639          |
| 1.6718        | 4.13  | 140000 | 1.6501          |
| 1.6562        | 4.71  | 160000 | 1.6350          |
| 1.6429        | 5.3   | 180000 | 1.6211          |
| 1.6313        | 5.89  | 200000 | 1.6102          |
| 1.6207        | 6.48  | 220000 | 1.6001          |
| 1.6099        | 7.07  | 240000 | 1.5902          |
| 1.6           | 7.66  | 260000 | 1.5799          |
| 1.5925        | 8.25  | 280000 | 1.5726          |
| 1.5847        | 8.84  | 300000 | 1.5645          |
| 1.5783        | 9.43  | 320000 | 1.5596          |
| 1.5712        | 10.02 | 340000 | 1.5510          |
| 1.5656        | 10.61 | 360000 | 1.5452          |
| 1.5598        | 11.2  | 380000 | 1.5410          |
| 1.5548        | 11.79 | 400000 | 1.5342          |
| 1.5497        | 12.38 | 420000 | 1.5293          |
| 1.546         | 12.96 | 440000 | 1.5241          |
| 1.5397        | 13.55 | 460000 | 1.5214          |
| 1.5365        | 14.14 | 480000 | 1.5164          |
| 1.5321        | 14.73 | 500000 | 1.5115          |
| 1.5285        | 15.32 | 520000 | 1.5075          |
| 1.5246        | 15.91 | 540000 | 1.5034          |
| 1.5217        | 16.5  | 560000 | 1.5029          |
| 1.5191        | 17.09 | 580000 | 1.4995          |
| 1.516         | 17.68 | 600000 | 1.4958          |


### 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_Zebrafish", "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\_Zebrafish
=======================


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


* Loss: 1.4958


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