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# conditional-detr-resnet-50_til-2023-cv-9

This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2502
- Loss Ce: 0.0010
- Loss Bbox: 0.0160
- Loss Giou: 0.0842
- Cardinality Error: 2.1237
- Map: 0.8063
- Map 50: 0.9901
- Map 75: 0.9609
- Map Small: 0.8063
- Map Medium: -1.0
- Map Large: -1.0
- Mar 1: 0.4097
- Mar 10: 0.8555
- Mar 100: 0.8555
- Mar Small: 0.8555
- Mar Medium: -1.0
- Mar Large: -1.0
- Map Per Class: -1.0
- Mar 100 Per Class: -1.0

## 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: 5e-05
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Loss Ce | Loss Bbox | Loss Giou | Cardinality Error | Map    | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1  | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Per Class | Mar 100 Per Class |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:---------:|:-----------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------------:|:-----------------:|
| 0.4695        | 1.0   | 708   | 0.4327          | 0.0120  | 0.0256    | 0.1404    | 2.1237            | 0.7356 | 0.9796 | 0.9229 | 0.7356    | -1.0       | -1.0      | 0.3810 | 0.7910 | 0.7910  | 0.7910    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2915        | 2.0   | 1416  | 0.3432          | 0.0056  | 0.0217    | 0.1118    | 2.1237            | 0.7640 | 0.9892 | 0.9391 | 0.7640    | -1.0       | -1.0      | 0.3900 | 0.8128 | 0.8128  | 0.8128    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2713        | 3.0   | 2124  | 0.3150          | 0.0063  | 0.0194    | 0.1026    | 2.1237            | 0.7819 | 0.9894 | 0.9494 | 0.7819    | -1.0       | -1.0      | 0.3977 | 0.8274 | 0.8274  | 0.8274    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2583        | 4.0   | 2832  | 0.2754          | 0.0026  | 0.0174    | 0.0915    | 2.1237            | 0.7931 | 0.9898 | 0.9515 | 0.7931    | -1.0       | -1.0      | 0.4026 | 0.8387 | 0.8387  | 0.8387    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2264        | 5.0   | 3540  | 0.2768          | 0.0019  | 0.0178    | 0.0921    | 2.1237            | 0.8011 | 0.9899 | 0.9623 | 0.8011    | -1.0       | -1.0      | 0.4057 | 0.8452 | 0.8452  | 0.8452    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2841        | 6.0   | 4248  | 0.3362          | 0.0049  | 0.0207    | 0.1115    | 2.1237            | 0.7973 | 0.9900 | 0.9614 | 0.7973    | -1.0       | -1.0      | 0.4043 | 0.8434 | 0.8434  | 0.8434    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2929        | 7.0   | 4956  | 0.3310          | 0.0078  | 0.0203    | 0.1071    | 2.1237            | 0.7986 | 0.9899 | 0.9616 | 0.7986    | -1.0       | -1.0      | 0.4053 | 0.8445 | 0.8445  | 0.8445    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2405        | 8.0   | 5664  | 0.2681          | 0.0017  | 0.0168    | 0.0904    | 2.1237            | 0.8018 | 0.9900 | 0.9619 | 0.8018    | -1.0       | -1.0      | 0.4067 | 0.8481 | 0.8481  | 0.8481    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.1851        | 9.0   | 6372  | 0.2680          | 0.0019  | 0.0168    | 0.0901    | 2.1237            | 0.8050 | 0.9900 | 0.9622 | 0.8050    | -1.0       | -1.0      | 0.4081 | 0.8511 | 0.8511  | 0.8511    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.1842        | 10.0  | 7080  | 0.2553          | 0.0013  | 0.0163    | 0.0856    | 2.1237            | 0.8074 | 0.9900 | 0.9627 | 0.8074    | -1.0       | -1.0      | 0.4095 | 0.8544 | 0.8544  | 0.8544    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.3201        | 11.0  | 7788  | 0.3556          | 0.0034  | 0.0226    | 0.1179    | 2.1237            | 0.8040 | 0.9900 | 0.9617 | 0.8040    | -1.0       | -1.0      | 0.4080 | 0.8511 | 0.8511  | 0.8511    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.266         | 12.0  | 8496  | 0.3296          | 0.0021  | 0.0191    | 0.1151    | 2.1237            | 0.7996 | 0.9900 | 0.9600 | 0.7996    | -1.0       | -1.0      | 0.4069 | 0.8489 | 0.8489  | 0.8489    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.2086        | 13.0  | 9204  | 0.2753          | 0.0016  | 0.0178    | 0.0916    | 2.1237            | 0.8007 | 0.9900 | 0.9603 | 0.8007    | -1.0       | -1.0      | 0.4076 | 0.8506 | 0.8506  | 0.8506    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.1853        | 14.0  | 9912  | 0.2452          | 0.0009  | 0.0156    | 0.0827    | 2.1237            | 0.8037 | 0.9900 | 0.9606 | 0.8037    | -1.0       | -1.0      | 0.4088 | 0.8533 | 0.8533  | 0.8533    | -1.0       | -1.0      | -1.0          | -1.0              |
| 0.1588        | 15.0  | 10620 | 0.2502          | 0.0010  | 0.0160    | 0.0842    | 2.1237            | 0.8063 | 0.9901 | 0.9609 | 0.8063    | -1.0       | -1.0      | 0.4097 | 0.8555 | 0.8555  | 0.8555    | -1.0       | -1.0      | -1.0          | -1.0              |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "conditional-detr-resnet-50_til-2023-cv-9", "results": []}]}
transformers tensorboard safetensors conditional_detr object-detection generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #tensorboard #safetensors #conditional_detr #object-detection #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

conditional-detr-resnet-50\_til-2023-cv-9
=========================================


This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2502
* Loss Ce: 0.0010
* Loss Bbox: 0.0160
* Loss Giou: 0.0842
* Cardinality Error: 2.1237
* Map: 0.8063
* Map 50: 0.9901
* Map 75: 0.9609
* Map Small: 0.8063
* Map Medium: -1.0
* Map Large: -1.0
* Mar 1: 0.4097
* Mar 10: 0.8555
* Mar 100: 0.8555
* Mar Small: 0.8555
* Mar Medium: -1.0
* Mar Large: -1.0
* Map Per Class: -1.0
* Mar 100 Per Class: -1.0


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: 5e-05
* 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: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #tensorboard #safetensors #conditional_detr #object-detection #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3