|
--- |
|
license: apache-2.0 |
|
base_model: facebook/deit-base-distilled-patch16-224 |
|
tags: |
|
- image-classification |
|
- vision |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: "DeiT-base-DatasetDict({\n train: Dataset({\n features: ['img',\ |
|
\ 'fine_label', 'coarse_label'],\n num_rows: 50000\n })\n test: Dataset({\n\ |
|
\ features: ['img', 'fine_label', 'coarse_label'],\n num_rows: 10000\n\ |
|
\ })\n validation: Dataset({\n features: ['img', 'fine_label', 'coarse_label'],\n\ |
|
\ num_rows: 10000\n })\n})" |
|
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. --> |
|
|
|
# DeiT-base-DatasetDict({ |
|
train: Dataset({ |
|
features: ['img', 'fine_label', 'coarse_label'], |
|
num_rows: 50000 |
|
}) |
|
test: Dataset({ |
|
features: ['img', 'fine_label', 'coarse_label'], |
|
num_rows: 10000 |
|
}) |
|
validation: Dataset({ |
|
features: ['img', 'fine_label', 'coarse_label'], |
|
num_rows: 10000 |
|
}) |
|
}) |
|
|
|
This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the cifar100 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3054 |
|
- Accuracy: 0.906 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 1 |
|
- seed: 777 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
|
|:-------------:|:-----:|:----:|:--------:|:---------------:| |
|
| 1.1232 | 1.0 | 782 | 0.8416 | 0.5390 | |
|
| 0.9017 | 2.0 | 1564 | 0.8699 | 0.4365 | |
|
| 0.7565 | 3.0 | 2346 | 0.8858 | 0.3678 | |
|
| 0.706 | 4.0 | 3128 | 0.8952 | 0.3446 | |
|
| 0.6353 | 5.0 | 3910 | 0.8986 | 0.3331 | |
|
| 0.5384 | 6.0 | 4692 | 0.9001 | 0.3223 | |
|
| 0.5004 | 7.0 | 5474 | 0.9018 | 0.3249 | |
|
| 0.4672 | 8.0 | 6256 | 0.904 | 0.3113 | |
|
| 0.4526 | 9.0 | 7038 | 0.9054 | 0.3081 | |
|
| 0.4289 | 10.0 | 7820 | 0.906 | 0.3054 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
