---
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: 1.7386
- Map: 0.021
- Map 50: 0.0429
- Map 75: 0.0201
- Map Small: 0.0058
- Map Medium: 0.0177
- Map Large: 0.0252
- Mar 1: 0.0523
- Mar 10: 0.1319
- Mar 100: 0.1741
- Mar Small: 0.0602
- Mar Medium: 0.1263
- Mar Large: 0.227
- Map Coverall: 0.0847
- Mar 100 Coverall: 0.4302
- Map Face Shield: 0.0035
- Mar 100 Face Shield: 0.0608
- Map Gloves: 0.0011
- Mar 100 Gloves: 0.1085
- Map Goggles: 0.001
- Mar 100 Goggles: 0.0292
- Map Mask: 0.0148
- Mar 100 Mask: 0.2418

## 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  | 1.9340          | 0.0138 | 0.0289 | 0.013  | 0.0007    | 0.013      | 0.0192    | 0.0285 | 0.081  | 0.1246  | 0.0206    | 0.0915     | 0.1533    | 0.0604       | 0.3464           | 0.0003          | 0.0354              | 0.0008     | 0.0915         | 0.001       | 0.0215          | 0.0067   | 0.128        |
| No log        | 2.0   | 214  | 1.7386          | 0.021  | 0.0429 | 0.0201 | 0.0058    | 0.0177     | 0.0252    | 0.0523 | 0.1319 | 0.1741  | 0.0602    | 0.1263     | 0.227     | 0.0847       | 0.4302           | 0.0035          | 0.0608              | 0.0011     | 0.1085         | 0.001       | 0.0292          | 0.0148   | 0.2418       |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0