|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224-in21k |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-base |
|
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. --> |
|
|
|
# vit-base |
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3177 |
|
- Accuracy: 0.4987 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.6698 | 1.0 | 48 | 1.5900 | 0.2539 | |
|
| 1.4981 | 2.0 | 96 | 1.4551 | 0.3835 | |
|
| 1.2747 | 3.0 | 144 | 1.3591 | 0.4408 | |
|
| 1.0701 | 4.0 | 192 | 1.3058 | 0.4902 | |
|
| 0.7885 | 5.0 | 240 | 1.3177 | 0.4987 | |
|
| 0.6023 | 6.0 | 288 | 1.3985 | 0.4870 | |
|
| 0.4814 | 7.0 | 336 | 1.4607 | 0.4824 | |
|
| 0.3708 | 8.0 | 384 | 1.5195 | 0.4720 | |
|
| 0.2755 | 9.0 | 432 | 1.5524 | 0.4798 | |
|
| 0.2476 | 10.0 | 480 | 1.5632 | 0.4792 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Tokenizers 0.19.1 |
|
|