---
license: apache-2.0
base_model: kacper-cierzniewski/daigram_detr_r50_albumentations
tags:
- generated_from_trainer
datasets:
- bpmn-shapes
model-index:
- name: daigram_detr_r50_albumentations_finetuning
  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. -->

# daigram_detr_r50_albumentations_finetuning

This model is a fine-tuned version of [kacper-cierzniewski/daigram_detr_r50_albumentations](https://huggingface.co/kacper-cierzniewski/daigram_detr_r50_albumentations) on the bpmn-shapes dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9817

## 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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9457        | 12.5  | 50   | 1.0238          |
| 0.9717        | 25.0  | 100  | 1.0411          |
| 0.9823        | 37.5  | 150  | 1.0269          |
| 0.9524        | 50.0  | 200  | 1.0518          |
| 0.9886        | 62.5  | 250  | 1.0548          |
| 0.9638        | 75.0  | 300  | 1.0454          |
| 0.948         | 87.5  | 350  | 1.0240          |
| 0.9312        | 100.0 | 400  | 1.0281          |
| 0.9183        | 112.5 | 450  | 1.0112          |
| 0.9219        | 125.0 | 500  | 1.0110          |
| 0.9285        | 137.5 | 550  | 1.0325          |
| 0.9177        | 150.0 | 600  | 1.0009          |
| 0.9323        | 162.5 | 650  | 1.0124          |
| 0.9333        | 175.0 | 700  | 1.0154          |
| 0.9386        | 187.5 | 750  | 1.0188          |
| 0.9586        | 200.0 | 800  | 0.9978          |
| 0.894         | 212.5 | 850  | 1.0087          |
| 0.8999        | 225.0 | 900  | 1.0055          |
| 0.9324        | 237.5 | 950  | 1.0185          |
| 0.9313        | 250.0 | 1000 | 0.9840          |
| 0.9177        | 262.5 | 1050 | 0.9785          |
| 0.8918        | 275.0 | 1100 | 0.9874          |
| 0.9145        | 287.5 | 1150 | 0.9802          |
| 0.89          | 300.0 | 1200 | 0.9879          |
| 0.8818        | 312.5 | 1250 | 0.9857          |
| 0.9256        | 325.0 | 1300 | 0.9951          |
| 0.9028        | 337.5 | 1350 | 1.0001          |
| 0.9252        | 350.0 | 1400 | 1.0033          |
| 0.9017        | 362.5 | 1450 | 0.9916          |
| 0.8783        | 375.0 | 1500 | 0.9858          |
| 0.911         | 387.5 | 1550 | 0.9758          |
| 0.8797        | 400.0 | 1600 | 0.9810          |
| 0.8995        | 412.5 | 1650 | 0.9840          |
| 0.8781        | 425.0 | 1700 | 0.9843          |
| 0.8897        | 437.5 | 1750 | 0.9745          |
| 0.905         | 450.0 | 1800 | 0.9825          |
| 0.8961        | 462.5 | 1850 | 0.9781          |
| 0.8865        | 475.0 | 1900 | 0.9781          |
| 0.8824        | 487.5 | 1950 | 0.9794          |
| 0.8836        | 500.0 | 2000 | 0.9817          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0