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# samolet_encoder_finetuned

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 ummagumm-a/samolet_frames dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1165

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3356        | 1.0   | 87   | 0.3257          |
| 0.2405        | 2.0   | 174  | 0.2403          |
| 0.1623        | 3.0   | 261  | 0.1606          |
| 0.1452        | 4.0   | 348  | 0.1454          |
| 0.1373        | 5.0   | 435  | 0.1413          |
| 0.1304        | 6.0   | 522  | 0.1369          |
| 0.129         | 7.0   | 609  | 0.1346          |
| 0.1291        | 8.0   | 696  | 0.1299          |
| 0.1277        | 9.0   | 783  | 0.1294          |
| 0.1244        | 10.0  | 870  | 0.1284          |
| 0.1275        | 11.0  | 957  | 0.1285          |
| 0.1196        | 12.0  | 1044 | 0.1264          |
| 0.1219        | 13.0  | 1131 | 0.1263          |
| 0.1195        | 14.0  | 1218 | 0.1265          |
| 0.1231        | 15.0  | 1305 | 0.1239          |
| 0.1208        | 16.0  | 1392 | 0.1216          |
| 0.118         | 17.0  | 1479 | 0.1223          |
| 0.1143        | 18.0  | 1566 | 0.1201          |
| 0.1177        | 19.0  | 1653 | 0.1198          |
| 0.1139        | 20.0  | 1740 | 0.1194          |
| 0.1152        | 21.0  | 1827 | 0.1193          |
| 0.1162        | 22.0  | 1914 | 0.1199          |
| 0.1113        | 23.0  | 2001 | 0.1183          |
| 0.1134        | 24.0  | 2088 | 0.1183          |
| 0.1136        | 25.0  | 2175 | 0.1184          |
| 0.1132        | 26.0  | 2262 | 0.1196          |
| 0.1156        | 27.0  | 2349 | 0.1185          |
| 0.1153        | 28.0  | 2436 | 0.1166          |
| 0.1139        | 29.0  | 2523 | 0.1153          |
| 0.1103        | 30.0  | 2610 | 0.1164          |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["masked-image-modeling", "generated_from_trainer"], "model-index": [{"name": "samolet_encoder_finetuned", "results": []}]}
transformers pytorch vit masked-image-modeling generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #masked-image-modeling #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

samolet\_encoder\_finetuned
===========================


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


* Loss: 0.1165


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: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #vit #masked-image-modeling #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3