Rfdetr Docvqa Media3 v2
This model is a fine-tuned version of Roboflow/rf-detr-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 16.2431 Map: 0.0037 Map 50: 0.0137 Map 75: 0.0004 Map Small: -1.0 Map...
Source du modèle
- Type
- Other
- Taille du fichier
- 122 MB
- Modèle de base
- Roboflow/rf-detr-base
- Version
- vRevision ef19ed0
- Mis à jour
- 16 sept. 2026
- Téléchargements
- 6
- Source
- Hugging Face
Description de la source
rfdetr-docvqa-media3-v2
This model is a fine-tuned version of Roboflow/rf-detr-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 16.2431
- Map: 0.0037
- Map 50: 0.0137
- Map 75: 0.0004
- Map Small: -1.0
- Map Medium: 0.0018
- Map Large: 0.0039
- Mar 1: 0.0203
- Mar 10: 0.0793
- Mar 100: 0.1731
- Mar Small: -1.0
- Mar Medium: 0.025
- Mar Large: 0.1816
- Map Chart: 0.0046
- Mar 100 Chart: 0.1474
- Map Image: 0.0062
- Mar 100 Image: 0.3269
- Map Signature: 0.0001
- Mar 100 Signature: 0.045
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_FUSED 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: 0.05
- num_epochs: 10
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 Chart | Mar 100 Chart | Map Image | Mar 100 Image | Map Signature | Mar 100 Signature |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 40.0459 | 1.0 | 33 | 25.5239 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0067 | -1.0 | 0.0 | 0.007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.02 |
| 15.4391 | 2.0 | 66 | 25.5408 | 0.0 | 0.0003 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | 0.003 | 0.003 | -1.0 | 0.0 | 0.0031 | 0.0 | 0.0053 | 0.0001 | 0.0038 | 0.0 | 0.0 |
| 13.9985 | 3.0 | 99 | 22.7635 | 0.0002 | 0.0004 | 0.0002 | -1.0 | 0.0 | 0.0002 | 0.007 | 0.0105 | 0.0155 | -1.0 | 0.0 | 0.0158 | 0.0006 | 0.0316 | 0.0 | 0.0 | 0.0 | 0.015 |
| 13.1759 | 4.0 | 132 | 21.8405 | 0.0013 | 0.0063 | 0.0 | -1.0 | 0.0 | 0.0013 | 0.0035 | 0.0233 | 0.0392 | -1.0 | 0.0 | 0.0412 | 0.0025 | 0.0421 | 0.0012 | 0.0654 | 0.0001 | 0.01 |
| 12.6280 | 5.0 | 165 | 21.5377 | 0.0015 | 0.0042 | 0.0011 | -1.0 | 0.0059 | 0.0015 | 0.0211 | 0.0228 | 0.1041 | -1.0 | 0.125 | 0.1001 | 0.0037 | 0.2 | 0.0008 | 0.0923 | 0.0 | 0.02 |
| 12.3205 | 6.0 | 198 | 19.0510 | 0.0012 | 0.0046 | 0.0004 | -1.0 | 0.0042 | 0.0012 | 0.0056 | 0.0642 | 0.1349 | -1.0 | 0.025 | 0.1397 | 0.0019 | 0.1579 | 0.0015 | 0.1769 | 0.0001 | 0.07 |
| 10.5714 | 7.0 | 231 | 16.7398 | 0.0023 | 0.01 | 0.0006 | -1.0 | 0.0134 | 0.0023 | 0.0158 | 0.0647 | 0.1626 | -1.0 | 0.15 | 0.1635 | 0.0049 | 0.1474 | 0.0021 | 0.3154 | 0.0001 | 0.025 |
| 10.2309 | 8.0 | 264 | 16.9129 | 0.0135 | 0.0575 | 0.0006 | -1.0 | 0.0072 | 0.0145 | 0.0126 | 0.0607 | 0.1619 | -1.0 | 0.075 | 0.1676 | 0.0125 | 0.1053 | 0.028 | 0.3154 | 0.0001 | 0.065 |
| 9.5882 | 9.0 | 297 | 16.5097 | 0.0138 | 0.0327 | 0.0006 | -1.0 | 0.0007 | 0.0142 | 0.0257 | 0.0652 | 0.1964 | -1.0 | 0.05 | 0.2046 | 0.034 | 0.1737 | 0.0073 | 0.3654 | 0.0001 | 0.05 |
| 9.5828 | 10.0 | 330 | 16.2431 | 0.0037 | 0.0137 | 0.0004 | -1.0 | 0.0018 | 0.0039 | 0.0203 | 0.0793 | 0.1731 | -1.0 | 0.025 | 0.1816 | 0.0046 | 0.1474 | 0.0062 | 0.3269 | 0.0001 | 0.045 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVérifié 1 sept.
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Artefacts du modèle
2 artefacts
Artefacts du modèle
2 artefactsExtraits de sources
2 extraits
Extraits de sources
2 extraits--- library_name: transformers license: apache-2.0 base_model: Roboflow/rf-detr-base tags: - generated_from_trainer model-index: - name: rfdetr-docvqa-media3-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. --> # rfdetr-docvqa-media3-v2 This model is a fine-tuned version of [Roboflow/rf-detr-base](https://huggingface.co/Roboflow/rf-detr-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 16.2431 - Map: 0.0037 - Map 50: 0.0137 - Map 75: 0.0004 - Map Small: -1.0 - Map Medium: 0.0018 - Map Large: 0.0039 - Mar 1: 0.0203 - Mar 10: 0.0793 - Mar 100: 0.1731 - Mar Small: -1.0 - Mar Medium: 0.025 - Mar Large: 0.1816 - Map Chart: 0.0046 - Mar 100 Chart: 0.1474 - Map Image: 0.0062 - Mar 100 Image: 0.3269 - Map Signature: 0.0001 - Mar 100 Signature: 0.045 ## 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_FUSED 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: 0.05 - num_epochs: 10 ### 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 Chart | Mar 100 Chart | Map Image | Mar 100 Image | Map Signature | Mar 100 Signature | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|:---------:|:-------------:|:-------------:|:-----------------:| | 40.0459 | 1.0 | 33 | 25.5239 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0067 | -1.0 | 0.0 | 0.007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.02 | | 15.4391 | 2.0 | 66 | 25.5408 | 0.0 | 0.0003 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | 0.003 | 0.003 | -1.0 | 0.0 | 0.0031 | 0.0 | 0.0053 | 0.0001 | 0.0038 | 0.0 | 0.0...
Source context: 6 downloads · 0 likes · Pipeline object-detection · Library transformers · Repo merve/rfdetr-docvqa-media3-v2
