---
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: 0.5846

## 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  | 2.5308          |
| 2.824         | 1.08  | 2000  | 2.0484          |
| 2.824         | 1.62  | 3000  | 1.7408          |
| 1.8911        | 2.16  | 4000  | 1.5862          |
| 1.8911        | 2.7   | 5000  | 1.4858          |
| 1.594         | 3.24  | 6000  | 1.3551          |
| 1.594         | 3.78  | 7000  | 1.2802          |
| 1.4147        | 4.32  | 8000  | 1.2439          |
| 1.4147        | 4.86  | 9000  | 1.1548          |
| 1.2978        | 5.4   | 10000 | 1.1031          |
| 1.2978        | 5.94  | 11000 | 1.0674          |
| 1.1984        | 6.48  | 12000 | 1.0380          |
| 1.1086        | 7.02  | 13000 | 0.9949          |
| 1.1086        | 7.56  | 14000 | 0.9393          |
| 1.0383        | 8.1   | 15000 | 0.9204          |
| 1.0383        | 8.64  | 16000 | 0.8921          |
| 0.9817        | 9.18  | 17000 | 0.8670          |
| 0.9817        | 9.72  | 18000 | 0.8250          |
| 0.9277        | 10.26 | 19000 | 0.8084          |
| 0.9277        | 10.8  | 20000 | 0.7968          |
| 0.8864        | 11.34 | 21000 | 0.7928          |
| 0.8864        | 11.88 | 22000 | 0.7605          |
| 0.8525        | 12.42 | 23000 | 0.7602          |
| 0.8525        | 12.96 | 24000 | 0.7406          |
| 0.8197        | 13.5  | 25000 | 0.7224          |
| 0.7975        | 14.04 | 26000 | 0.7060          |
| 0.7975        | 14.58 | 27000 | 0.6893          |
| 0.7733        | 15.12 | 28000 | 0.6940          |
| 0.7733        | 15.66 | 29000 | 0.6836          |
| 0.7534        | 16.2  | 30000 | 0.6620          |
| 0.7534        | 16.74 | 31000 | 0.6584          |
| 0.7376        | 17.28 | 32000 | 0.6552          |
| 0.7376        | 17.82 | 33000 | 0.6487          |
| 0.7242        | 18.36 | 34000 | 0.6334          |
| 0.7242        | 18.9  | 35000 | 0.6319          |
| 0.7052        | 19.44 | 36000 | 0.6223          |
| 0.7052        | 19.98 | 37000 | 0.6155          |
| 0.6935        | 20.52 | 38000 | 0.6092          |
| 0.6816        | 21.06 | 39000 | 0.6079          |
| 0.6816        | 21.6  | 40000 | 0.6045          |
| 0.6747        | 22.14 | 41000 | 0.5997          |
| 0.6747        | 22.68 | 42000 | 0.6002          |
| 0.6693        | 23.22 | 43000 | 0.5924          |
| 0.6693        | 23.76 | 44000 | 0.5922          |
| 0.6608        | 24.3  | 45000 | 0.5861          |
| 0.6608        | 24.84 | 46000 | 0.5846          |


### Framework versions

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