---
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: queue_detection
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# queue_detection

This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4686
- Map: 0.2556
- Map 50: 0.4262
- Map 75: 0.2687
- Map Small: -1.0
- Map Medium: 0.0006
- Map Large: 0.2572
- Mar 1: 0.2033
- Mar 10: 0.561
- Mar 100: 0.715
- Mar Small: -1.0
- Mar Medium: 0.0036
- Mar Large: 0.7212
- Map Cashier: 0.3957
- Mar 100 Cashier: 0.812
- Map Cx: 0.1154
- Mar 100 Cx: 0.618

## 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: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Map    | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1  | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Cashier | Mar 100 Cashier | Map Cx | Mar 100 Cx |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-----------:|:---------------:|:------:|:----------:|
| No log        | 1.0   | 218  | 1.6672          | 0.1422 | 0.2781 | 0.1441 | -1.0      | 0.0        | 0.1427    | 0.166  | 0.421  | 0.6116  | -1.0      | 0.0        | 0.6154    | 0.2345      | 0.7322          | 0.05   | 0.4911     |
| No log        | 2.0   | 436  | 1.4686          | 0.2556 | 0.4262 | 0.2687 | -1.0      | 0.0006     | 0.2572    | 0.2033 | 0.561  | 0.715   | -1.0      | 0.0036     | 0.7212    | 0.3957      | 0.812           | 0.1154 | 0.618      |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cpu
- Datasets 2.20.0
- Tokenizers 0.19.1