|
|
---
|
|
|
library_name: transformers
|
|
|
license: apache-2.0
|
|
|
base_model: microsoft/conditional-detr-resnet-50
|
|
|
tags:
|
|
|
- generated_from_trainer
|
|
|
model-index:
|
|
|
- name: results
|
|
|
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. -->
|
|
|
|
|
|
# results
|
|
|
|
|
|
This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
|
|
|
It achieves the following results on the evaluation set:
|
|
|
- Loss: 1.7669
|
|
|
|
|
|
## 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: 2e-05
|
|
|
- train_batch_size: 16
|
|
|
- eval_batch_size: 16
|
|
|
- seed: 42
|
|
|
- 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: linear
|
|
|
- num_epochs: 30
|
|
|
|
|
|
### Training results
|
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss |
|
|
|
|:-------------:|:-----:|:----:|:---------------:|
|
|
|
| 12.8436 | 1.0 | 4 | 11.5652 |
|
|
|
| 12.8436 | 2.0 | 8 | 8.6499 |
|
|
|
| 12.8436 | 3.0 | 12 | 6.6430 |
|
|
|
| 12.8436 | 4.0 | 16 | 5.4425 |
|
|
|
| 12.8436 | 5.0 | 20 | 4.4521 |
|
|
|
| 12.8436 | 6.0 | 24 | 3.9127 |
|
|
|
| 12.8436 | 7.0 | 28 | 3.3273 |
|
|
|
| 12.8436 | 8.0 | 32 | 3.0743 |
|
|
|
| 12.8436 | 9.0 | 36 | 2.8087 |
|
|
|
| 12.8436 | 10.0 | 40 | 2.5618 |
|
|
|
| 12.8436 | 11.0 | 44 | 2.4515 |
|
|
|
| 12.8436 | 12.0 | 48 | 2.3580 |
|
|
|
| 12.8436 | 13.0 | 52 | 2.2749 |
|
|
|
| 12.8436 | 14.0 | 56 | 2.1216 |
|
|
|
| 12.8436 | 15.0 | 60 | 2.0890 |
|
|
|
| 12.8436 | 16.0 | 64 | 2.0283 |
|
|
|
| 12.8436 | 17.0 | 68 | 2.0358 |
|
|
|
| 12.8436 | 18.0 | 72 | 1.9374 |
|
|
|
| 12.8436 | 19.0 | 76 | 1.9090 |
|
|
|
| 12.8436 | 20.0 | 80 | 1.8779 |
|
|
|
| 12.8436 | 21.0 | 84 | 1.8474 |
|
|
|
| 12.8436 | 22.0 | 88 | 1.8371 |
|
|
|
| 12.8436 | 23.0 | 92 | 1.8247 |
|
|
|
| 12.8436 | 24.0 | 96 | 1.8031 |
|
|
|
| 12.8436 | 25.0 | 100 | 1.7836 |
|
|
|
| 12.8436 | 26.0 | 104 | 1.7500 |
|
|
|
| 12.8436 | 27.0 | 108 | 1.7332 |
|
|
|
| 12.8436 | 28.0 | 112 | 1.7477 |
|
|
|
| 12.8436 | 29.0 | 116 | 1.7634 |
|
|
|
| 12.8436 | 30.0 | 120 | 1.7669 |
|
|
|
|
|
|
|
|
|
### Framework versions
|
|
|
|
|
|
- Transformers 4.49.0
|
|
|
- Pytorch 2.6.0+cpu
|
|
|
- Datasets 3.3.2
|
|
|
- Tokenizers 0.21.0
|
|
|
|
