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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: 2.3956
- Map: 0.0065
- Map 50: 0.0182
- Map 75: 0.0036
- Map Small: 0.0006
- Map Medium: 0.014
- Map Large: 0.007
- Mar 1: 0.0123
- Mar 10: 0.0366
- Mar 100: 0.067
- Mar Small: 0.0072
- Mar Medium: 0.0388
- Mar Large: 0.0714
- Map Coverall: 0.0323
- Mar 100 Coverall: 0.3018
- Map Face Shield: 0.0
- Mar 100 Face Shield: 0.0
- Map Gloves: 0.0001
- Mar 100 Gloves: 0.0165
- Map Goggles: 0.0
- Mar 100 Goggles: 0.0062
- Map Mask: 0.0
- Mar 100 Mask: 0.0107
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3
### 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 | 2.6211 | 0.0025 | 0.0088 | 0.0008 | 0.0 | 0.008 | 0.0025 | 0.0098 | 0.0172 | 0.0569 | 0.0 | 0.0309 | 0.0621 | 0.0124 | 0.2802 | 0.0 | 0.0025 | 0.0 | 0.0004 | 0.0 | 0.0015 | 0.0 | 0.0 |
| No log | 2.0 | 214 | 2.4397 | 0.0058 | 0.0156 | 0.0032 | 0.0004 | 0.014 | 0.0062 | 0.0081 | 0.0352 | 0.0525 | 0.0098 | 0.0338 | 0.0524 | 0.0287 | 0.2297 | 0.0 | 0.0 | 0.0001 | 0.029 | 0.0 | 0.0 | 0.0 | 0.0036 |
| No log | 3.0 | 321 | 2.3956 | 0.0065 | 0.0182 | 0.0036 | 0.0006 | 0.014 | 0.007 | 0.0123 | 0.0366 | 0.067 | 0.0072 | 0.0388 | 0.0714 | 0.0323 | 0.3018 | 0.0 | 0.0 | 0.0001 | 0.0165 | 0.0 | 0.0062 | 0.0 | 0.0107 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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