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# yolos-tiny-CD45RB-1000-att

This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co/hustvl/yolos-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6170

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.5369        | 1.0   | 94   | 2.7680          |
| 3.4721        | 2.0   | 188  | 2.7605          |
| 3.4243        | 3.0   | 282  | 2.6854          |
| 3.3027        | 4.0   | 376  | 2.6661          |
| 3.2875        | 5.0   | 470  | 2.6692          |
| 3.2959        | 6.0   | 564  | 2.6477          |
| 3.2286        | 7.0   | 658  | 2.6885          |
| 3.1364        | 8.0   | 752  | 2.6583          |
| 3.0872        | 9.0   | 846  | 2.6667          |
| 3.0935        | 10.0  | 940  | 2.6170          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "yolos-tiny-CD45RB-1000-att", "results": []}]}
transformers pytorch tensorboard yolos object-detection generated_from_trainer license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #yolos #object-detection #generated_from_trainer #license-apache-2.0 #endpoints_compatible #has_space #region-us 

yolos-tiny-CD45RB-1000-att
==========================


This model is a fine-tuned version of hustvl/yolos-tiny on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.6170


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: 0.0001
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #yolos #object-detection #generated_from_trainer #license-apache-2.0 #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #yolos #object-detection #generated_from_trainer #license-apache-2.0 #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2