|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/deformable-detr-detic |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- generator |
|
model-index: |
|
- name: fisheye8k_facebook_deformable-detr-detic |
|
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. --> |
|
|
|
# fisheye8k_facebook_deformable-detr-detic |
|
|
|
This model is a fine-tuned version of [facebook/deformable-detr-detic](https://huggingface.co/facebook/deformable-detr-detic) on the generator dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.1348 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 8 |
|
- seed: 0 |
|
- 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 |
|
- num_epochs: 36 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
| 2.435 | 1.0 | 5288 | 2.4832 | |
|
| 2.2626 | 2.0 | 10576 | 2.6324 | |
|
| 1.8443 | 3.0 | 15864 | 2.1361 | |
|
| 2.4834 | 4.0 | 21152 | 2.5269 | |
|
| 2.3417 | 5.0 | 26440 | 2.5997 | |
|
| 1.939 | 6.0 | 31728 | 2.1948 | |
|
| 1.8384 | 7.0 | 37016 | 2.0057 | |
|
| 1.7235 | 8.0 | 42304 | 2.0182 | |
|
| 1.728 | 9.0 | 47592 | 1.9454 | |
|
| 1.621 | 10.0 | 52880 | 1.9876 | |
|
| 1.539 | 11.0 | 58168 | 1.8862 | |
|
| 1.7229 | 12.0 | 63456 | 2.2071 | |
|
| 1.9613 | 13.0 | 68744 | 2.5147 | |
|
| 1.5238 | 14.0 | 74032 | 1.9836 | |
|
| 1.5777 | 15.0 | 79320 | 2.0812 | |
|
| 1.5963 | 16.0 | 84608 | 2.1348 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.3 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
