|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-hybrid-base-bit-384 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hybrid-cnn-vit |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8707767328456983 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# hybrid-cnn-vit |
|
|
|
This model is a fine-tuned version of [google/vit-hybrid-base-bit-384](https://huggingface.co/google/vit-hybrid-base-bit-384) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3384 |
|
- Accuracy: 0.8708 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.5277 | 1.0 | 202 | 0.3903 | 0.8210 | |
|
| 0.4623 | 2.0 | 404 | 0.3478 | 0.8415 | |
|
| 0.4497 | 3.0 | 606 | 0.3334 | 0.8520 | |
|
| 0.4074 | 4.0 | 808 | 0.3397 | 0.8460 | |
|
| 0.3552 | 5.0 | 1010 | 0.3227 | 0.8624 | |
|
| 0.3637 | 6.0 | 1212 | 0.3230 | 0.8617 | |
|
| 0.3316 | 7.0 | 1414 | 0.3189 | 0.8673 | |
|
| 0.31 | 8.0 | 1616 | 0.3804 | 0.8492 | |
|
| 0.2324 | 9.0 | 1818 | 0.3382 | 0.8662 | |
|
| 0.234 | 10.0 | 2020 | 0.3384 | 0.8708 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
