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# human-actions-vit-model-francomedin

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 8.2276
- Accuracy: 0.0631

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3325        | 0.32  | 500  | 4.2477          | 0.0298   |
| 0.9863        | 0.63  | 1000 | 3.6803          | 0.1269   |
| 0.8753        | 0.95  | 1500 | 4.7335          | 0.0443   |
| 0.5808        | 1.27  | 2000 | 5.3964          | 0.0752   |
| 0.5256        | 1.59  | 2500 | 5.2087          | 0.1059   |
| 0.5277        | 1.9   | 3000 | 5.7696          | 0.0783   |
| 0.326         | 2.22  | 3500 | 6.5902          | 0.0348   |
| 0.2548        | 2.54  | 4000 | 6.4781          | 0.0961   |
| 0.2708        | 2.86  | 4500 | 6.2750          | 0.0933   |
| 0.1677        | 3.17  | 5000 | 7.2354          | 0.0763   |
| 0.0796        | 3.49  | 5500 | 7.6928          | 0.0633   |
| 0.0904        | 3.81  | 6000 | 7.5144          | 0.0607   |
| 0.0561        | 4.13  | 6500 | 7.9617          | 0.0665   |
| 0.0205        | 4.44  | 7000 | 7.9271          | 0.0681   |
| 0.0204        | 4.76  | 7500 | 8.2276          | 0.0631   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "human-actions-vit-model-francomedin", "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 

human-actions-vit-model-francomedin
===================================


This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 8.2276
* Accuracy: 0.0631


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: 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: 5


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 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: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3