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# exper_batch_32_e4

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the sudo-s/herbier_mesuem1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3909
- Accuracy: 0.9067

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Apex, opt level O1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.4295        | 0.31  | 100  | 3.4027          | 0.2837   |
| 2.5035        | 0.62  | 200  | 2.4339          | 0.5247   |
| 1.6542        | 0.94  | 300  | 1.7690          | 0.6388   |
| 1.1589        | 1.25  | 400  | 1.3106          | 0.7460   |
| 0.9363        | 1.56  | 500  | 0.9977          | 0.7803   |
| 0.6946        | 1.88  | 600  | 0.8138          | 0.8207   |
| 0.3488        | 2.19  | 700  | 0.6593          | 0.8489   |
| 0.2935        | 2.5   | 800  | 0.5725          | 0.8662   |
| 0.2557        | 2.81  | 900  | 0.5088          | 0.8855   |
| 0.1509        | 3.12  | 1000 | 0.4572          | 0.8971   |
| 0.1367        | 3.44  | 1100 | 0.4129          | 0.9090   |
| 0.1078        | 3.75  | 1200 | 0.3909          | 0.9067   |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.5.1
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "exper_batch_32_e4", "results": []}]}
transformers pytorch tensorboard vit image-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

exper\_batch\_32\_e4
====================


This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the sudo-s/herbier\_mesuem1 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3909
* Accuracy: 0.9067


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: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* mixed\_precision\_training: Apex, opt level O1


### Training results



### Framework versions


* Transformers 4.19.4
* Pytorch 1.5.1
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* mixed\_precision\_training: Apex, opt level O1 ### Training results ### Framework versions


* Transformers 4.19.4
* Pytorch 1.5.1
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* mixed\_precision\_training: Apex, opt level O1 ### Training results ### Framework versions


* Transformers 4.19.4
* Pytorch 1.5.1
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* mixed\_precision\_training: Apex, opt level O1### Training results### Framework versions


* Transformers 4.19.4
* Pytorch 1.5.1
* Datasets 2.3.2
* Tokenizers 0.12.1