|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/detr-resnet-50 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: chickens |
|
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. --> |
|
|
|
# chickens |
|
|
|
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: 0.6675 |
|
|
|
## 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: cosine |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 13 | 0.9785 | |
|
| No log | 2.0 | 26 | 0.9392 | |
|
| 1.1336 | 3.0 | 39 | 0.8768 | |
|
| 1.1336 | 4.0 | 52 | 0.8375 | |
|
| 0.9422 | 5.0 | 65 | 0.8428 | |
|
| 0.9422 | 6.0 | 78 | 0.8161 | |
|
| 0.8703 | 7.0 | 91 | 0.7947 | |
|
| 0.8703 | 8.0 | 104 | 0.7691 | |
|
| 0.8703 | 9.0 | 117 | 0.7788 | |
|
| 0.8332 | 10.0 | 130 | 0.7683 | |
|
| 0.8332 | 11.0 | 143 | 0.7432 | |
|
| 0.7978 | 12.0 | 156 | 0.7431 | |
|
| 0.7978 | 13.0 | 169 | 0.7229 | |
|
| 0.7796 | 14.0 | 182 | 0.7483 | |
|
| 0.7796 | 15.0 | 195 | 0.7237 | |
|
| 0.7796 | 16.0 | 208 | 0.7092 | |
|
| 0.7763 | 17.0 | 221 | 0.7036 | |
|
| 0.7763 | 18.0 | 234 | 0.7014 | |
|
| 0.749 | 19.0 | 247 | 0.6938 | |
|
| 0.749 | 20.0 | 260 | 0.6885 | |
|
| 0.742 | 21.0 | 273 | 0.6886 | |
|
| 0.742 | 22.0 | 286 | 0.6793 | |
|
| 0.742 | 23.0 | 299 | 0.6723 | |
|
| 0.7268 | 24.0 | 312 | 0.6708 | |
|
| 0.7268 | 25.0 | 325 | 0.6694 | |
|
| 0.7258 | 26.0 | 338 | 0.6672 | |
|
| 0.7258 | 27.0 | 351 | 0.6674 | |
|
| 0.7074 | 28.0 | 364 | 0.6673 | |
|
| 0.7074 | 29.0 | 377 | 0.6671 | |
|
| 0.7168 | 30.0 | 390 | 0.6675 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.19.1 |
|
|
