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---
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
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