---
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr-amzss3-v2
  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-amzss3-v2

This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3494

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 0.54  | 1000  | 0.4810          |
| 0.5325        | 1.08  | 2000  | 0.4812          |
| 0.5325        | 1.62  | 3000  | 0.4739          |
| 0.5322        | 2.16  | 4000  | 0.4759          |
| 0.5322        | 2.7   | 5000  | 0.4818          |
| 0.5259        | 3.24  | 6000  | 0.4522          |
| 0.5259        | 3.78  | 7000  | 0.4632          |
| 0.5167        | 4.32  | 8000  | 0.4628          |
| 0.5167        | 4.86  | 9000  | 0.4345          |
| 0.5076        | 5.4   | 10000 | 0.4563          |
| 0.5076        | 5.94  | 11000 | 0.4326          |
| 0.494         | 6.48  | 12000 | 0.4424          |
| 0.4906        | 7.02  | 13000 | 0.4272          |
| 0.4906        | 7.56  | 14000 | 0.4164          |
| 0.4801        | 8.1   | 15000 | 0.4213          |
| 0.4801        | 8.64  | 16000 | 0.4320          |
| 0.4699        | 9.18  | 17000 | 0.4100          |
| 0.4699        | 9.72  | 18000 | 0.4127          |
| 0.4613        | 10.26 | 19000 | 0.4035          |
| 0.4613        | 10.8  | 20000 | 0.4039          |
| 0.4556        | 11.34 | 21000 | 0.4149          |
| 0.4556        | 11.88 | 22000 | 0.4092          |
| 0.4475        | 12.42 | 23000 | 0.3965          |
| 0.4475        | 12.96 | 24000 | 0.3973          |
| 0.4389        | 13.5  | 25000 | 0.4013          |
| 0.4349        | 14.04 | 26000 | 0.3797          |
| 0.4349        | 14.58 | 27000 | 0.3728          |
| 0.4288        | 15.12 | 28000 | 0.3834          |
| 0.4288        | 15.66 | 29000 | 0.3885          |
| 0.4222        | 16.2  | 30000 | 0.3820          |
| 0.4222        | 16.74 | 31000 | 0.3755          |
| 0.4152        | 17.28 | 32000 | 0.3693          |
| 0.4152        | 17.82 | 33000 | 0.3679          |
| 0.4122        | 18.36 | 34000 | 0.3605          |
| 0.4122        | 18.9  | 35000 | 0.3625          |
| 0.4077        | 19.44 | 36000 | 0.3631          |
| 0.4077        | 19.98 | 37000 | 0.3607          |
| 0.4           | 20.52 | 38000 | 0.3615          |
| 0.3972        | 21.06 | 39000 | 0.3561          |
| 0.3972        | 21.6  | 40000 | 0.3594          |
| 0.3953        | 22.14 | 41000 | 0.3554          |
| 0.3953        | 22.68 | 42000 | 0.3515          |
| 0.3903        | 23.22 | 43000 | 0.3539          |
| 0.3903        | 23.76 | 44000 | 0.3500          |
| 0.3878        | 24.3  | 45000 | 0.3489          |
| 0.3878        | 24.84 | 46000 | 0.3494          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3