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# plant-seedlings-model-freeze-2

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1729
- Accuracy: 0.9720

## 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: 16
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0346        | 0.25  | 100  | 0.2971          | 0.9573   |
| 0.158         | 0.51  | 200  | 0.3343          | 0.9452   |
| 0.0218        | 0.76  | 300  | 0.5939          | 0.9051   |
| 0.0525        | 1.02  | 400  | 0.3253          | 0.9446   |
| 0.0177        | 1.27  | 500  | 0.3484          | 0.9465   |
| 0.034         | 1.53  | 600  | 0.1919          | 0.9637   |
| 0.001         | 1.78  | 700  | 0.1797          | 0.9643   |
| 0.0093        | 2.04  | 800  | 0.1854          | 0.9682   |
| 0.0598        | 2.29  | 900  | 0.2082          | 0.9624   |
| 0.0008        | 2.54  | 1000 | 0.2089          | 0.9567   |
| 0.0501        | 2.8   | 1100 | 0.2640          | 0.9567   |
| 0.0015        | 3.05  | 1200 | 0.1899          | 0.9650   |
| 0.0431        | 3.31  | 1300 | 0.1866          | 0.9669   |
| 0.007         | 3.56  | 1400 | 0.1962          | 0.9707   |
| 0.005         | 3.82  | 1500 | 0.2161          | 0.9624   |
| 0.0009        | 4.07  | 1600 | 0.1618          | 0.9656   |
| 0.0011        | 4.33  | 1700 | 0.1340          | 0.9662   |
| 0.0008        | 4.58  | 1800 | 0.1606          | 0.9688   |
| 0.0221        | 4.83  | 1900 | 0.1498          | 0.9707   |
| 0.0085        | 5.09  | 2000 | 0.2956          | 0.9490   |
| 0.0018        | 5.34  | 2100 | 0.1322          | 0.9745   |
| 0.0002        | 5.6   | 2200 | 0.2376          | 0.9592   |
| 0.0285        | 5.85  | 2300 | 0.1476          | 0.9707   |
| 0.0001        | 6.11  | 2400 | 0.1968          | 0.9618   |
| 0.0           | 6.36  | 2500 | 0.1780          | 0.9656   |
| 0.0001        | 6.62  | 2600 | 0.1731          | 0.9682   |
| 0.0           | 6.87  | 2700 | 0.1729          | 0.9694   |
| 0.0           | 7.12  | 2800 | 0.1684          | 0.9713   |
| 0.0           | 7.38  | 2900 | 0.1692          | 0.9713   |
| 0.0           | 7.63  | 3000 | 0.1699          | 0.9713   |
| 0.0           | 7.89  | 3100 | 0.1708          | 0.9713   |
| 0.0           | 8.14  | 3200 | 0.1708          | 0.9720   |
| 0.0           | 8.4   | 3300 | 0.1712          | 0.9720   |
| 0.0           | 8.65  | 3400 | 0.1718          | 0.9720   |
| 0.0           | 8.91  | 3500 | 0.1721          | 0.9720   |
| 0.0           | 9.16  | 3600 | 0.1725          | 0.9720   |
| 0.0           | 9.41  | 3700 | 0.1727          | 0.9720   |
| 0.0           | 9.67  | 3800 | 0.1728          | 0.9720   |
| 0.0           | 9.92  | 3900 | 0.1729          | 0.9720   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "model-index": [{"name": "plant-seedlings-model-freeze-2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9719745222929936, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard vit image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

plant-seedlings-model-freeze-2
==============================


This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1729
* Accuracy: 0.9720


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: 16
* 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
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* 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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* 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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* 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
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3