---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: output
  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. -->

# output

This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9020

## 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: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 375
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8809        | 1.0   | 250  | 1.6853          |
| 1.4938        | 2.0   | 500  | 1.3327          |
| 1.3403        | 3.0   | 750  | 1.2940          |
| 1.3485        | 4.0   | 1000 | 1.2512          |
| 1.2645        | 5.0   | 1250 | 1.2189          |
| 1.2061        | 6.0   | 1500 | 1.1517          |
| 1.1632        | 7.0   | 1750 | 1.1042          |
| 1.179         | 8.0   | 2000 | 1.0796          |
| 1.1558        | 9.0   | 2250 | 1.0567          |
| 1.1294        | 10.0  | 2500 | 1.0661          |
| 1.0644        | 11.0  | 2750 | 1.0214          |
| 1.0545        | 12.0  | 3000 | 1.0508          |
| 1.0455        | 13.0  | 3250 | 0.9904          |
| 1.0242        | 14.0  | 3500 | 0.9863          |
| 1.0021        | 15.0  | 3750 | 0.9897          |
| 0.9947        | 16.0  | 4000 | 0.9774          |
| 0.9456        | 17.0  | 4250 | 0.9485          |
| 0.9339        | 18.0  | 4500 | 0.9553          |
| 0.9481        | 19.0  | 4750 | 0.9431          |
| 0.8992        | 20.0  | 5000 | 0.9348          |
| 0.8792        | 21.0  | 5250 | 0.9265          |
| 0.8946        | 22.0  | 5500 | 0.9271          |
| 0.8913        | 23.0  | 5750 | 0.9249          |
| 0.8813        | 24.0  | 6000 | 0.9072          |
| 0.885         | 25.0  | 6250 | 0.9115          |
| 0.8477        | 26.0  | 6500 | 0.9091          |
| 0.8792        | 27.0  | 6750 | 0.9045          |
| 0.8816        | 28.0  | 7000 | 0.9034          |
| 0.8633        | 29.0  | 7250 | 0.9005          |
| 0.8921        | 30.0  | 7500 | 0.9102          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1