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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: 1.7756
- 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
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