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# vit-model

This model is a fine-tuned version of [](https://huggingface.co/) on the preprocessed1024_config dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1353
- Accuracy: {'accuracy': 0.6011306532663316}
- F1: {'f1': 0.5956396413406886}

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                          |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:---------------------------:|
| 1.224         | 1.0   | 796  | 0.9884          | {'accuracy': 0.5276381909547738} | {'f1': 0.40344173017767304} |
| 0.96          | 2.0   | 1592 | 0.9255          | {'accuracy': 0.5621859296482412} | {'f1': 0.5134011716404221}  |
| 0.8878        | 3.0   | 2388 | 0.9308          | {'accuracy': 0.574748743718593}  | {'f1': 0.46867195041352344} |
| 0.809         | 4.0   | 3184 | 0.8904          | {'accuracy': 0.6067839195979899} | {'f1': 0.5799288651427482}  |
| 0.7541        | 5.0   | 3980 | 0.8936          | {'accuracy': 0.5954773869346733} | {'f1': 0.5938876317530138}  |
| 0.6904        | 6.0   | 4776 | 0.8760          | {'accuracy': 0.6118090452261307} | {'f1': 0.6023012293668115}  |
| 0.6195        | 7.0   | 5572 | 1.0032          | {'accuracy': 0.5917085427135679} | {'f1': 0.5834559014249068}  |
| 0.5766        | 8.0   | 6368 | 1.0268          | {'accuracy': 0.6023869346733668} | {'f1': 0.5779800559497847}  |
| 0.4963        | 9.0   | 7164 | 1.0460          | {'accuracy': 0.5992462311557789} | {'f1': 0.5875334711293277}  |
| 0.4323        | 10.0  | 7960 | 1.1353          | {'accuracy': 0.6011306532663316} | {'f1': 0.5956396413406886}  |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["preprocessed1024_config"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "vit-model", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "preprocessed1024_config", "type": "preprocessed1024_config", "args": "default"}, "metrics": [{"type": "accuracy", "value": {"accuracy": 0.6011306532663316}, "name": "Accuracy"}, {"type": "f1", "value": {"f1": 0.5956396413406886}, "name": "F1"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:preprocessed1024_config model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-preprocessed1024_config #model-index #autotrain_compatible #endpoints_compatible #region-us 

vit-model
=========


This model is a fine-tuned version of [](URL on the preprocessed1024\_config dataset.
It achieves the following results on the evaluation set:


* Loss: 1.1353
* Accuracy: {'accuracy': 0.6011306532663316}
* F1: {'f1': 0.5956396413406886}


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-preprocessed1024_config #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1