---
library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr_finetuned_cppe5
  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. -->

# detr_finetuned_cppe5

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: 1.7756
- Map: 0.0254
- Map 50: 0.0575
- Map 75: 0.0211
- Map Small: 0.015
- Map Medium: 0.0121
- Map Large: 0.0356
- Mar 1: 0.0618
- Mar 10: 0.1553
- Mar 100: 0.1996
- Mar Small: 0.0818
- Mar Medium: 0.1728
- Mar Large: 0.2326
- Map Coverall: 0.0809
- Mar 100 Coverall: 0.4441
- Map Face Shield: 0.0051
- Mar 100 Face Shield: 0.1025
- Map Gloves: 0.0031
- Mar 100 Gloves: 0.1482
- Map Goggles: 0.0022
- Mar 100 Goggles: 0.0585
- Map Mask: 0.0358
- Mar 100 Mask: 0.2444

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 2

### 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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| No log        | 1.0   | 107  | 1.9010          | 0.0125 | 0.0389 | 0.0069 | 0.0123    | 0.0077     | 0.0195    | 0.036  | 0.0972 | 0.1374  | 0.0633    | 0.1291     | 0.1645    | 0.0309       | 0.2302           | 0.0065          | 0.1076              | 0.0022     | 0.1348         | 0.0002      | 0.0077          | 0.0225   | 0.2067       |
| No log        | 2.0   | 214  | 1.7756          | 0.0254 | 0.0575 | 0.0211 | 0.015     | 0.0121     | 0.0356    | 0.0618 | 0.1553 | 0.1996  | 0.0818    | 0.1728     | 0.2326    | 0.0809       | 0.4441           | 0.0051          | 0.1025              | 0.0031     | 0.1482         | 0.0022      | 0.0585          | 0.0358   | 0.2444       |


### Framework versions

- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4