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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MyPetModel
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/2zsefy9c)
# MyPetModel
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4452
- Accuracy: 0.7787
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.4374 | 0.2278 | 100 | 0.4457 | 0.7826 |
| 0.2148 | 0.4556 | 200 | 0.4591 | 0.7908 |
| 0.0794 | 0.6834 | 300 | 0.5510 | 0.8048 |
| 0.0433 | 0.9112 | 400 | 0.5158 | 0.8157 |
| 0.029 | 1.1390 | 500 | 0.8849 | 0.7725 |
| 0.0181 | 1.3667 | 600 | 0.7288 | 0.8135 |
| 0.0126 | 1.5945 | 700 | 0.6898 | 0.8206 |
| 0.0112 | 1.8223 | 800 | 0.9681 | 0.7703 |
| 0.0084 | 2.0501 | 900 | 0.9025 | 0.7846 |
| 0.0088 | 2.2779 | 1000 | 1.0068 | 0.7766 |
| 0.0046 | 2.5057 | 1100 | 0.8545 | 0.8148 |
| 0.0033 | 2.7335 | 1200 | 1.0199 | 0.7904 |
| 0.0036 | 2.9613 | 1300 | 1.3595 | 0.7381 |
| 0.005 | 3.1891 | 1400 | 1.3578 | 0.7361 |
| 0.0051 | 3.4169 | 1500 | 0.9367 | 0.8104 |
| 0.0021 | 3.6446 | 1600 | 1.6113 | 0.7173 |
| 0.0036 | 3.8724 | 1700 | 0.6898 | 0.8617 |
| 0.0026 | 4.1002 | 1800 | 1.0784 | 0.7958 |
| 0.0041 | 4.3280 | 1900 | 1.6640 | 0.7018 |
| 0.0054 | 4.5558 | 2000 | 0.9458 | 0.8047 |
| 0.0012 | 4.7836 | 2100 | 1.3136 | 0.7621 |
| 0.0047 | 5.0114 | 2200 | 1.7060 | 0.7058 |
| 0.0036 | 5.2392 | 2300 | 1.2863 | 0.7700 |
| 0.0023 | 5.4670 | 2400 | 1.1671 | 0.7861 |
| 0.0034 | 5.6948 | 2500 | 1.1628 | 0.7908 |
| 0.0022 | 5.9226 | 2600 | 1.2225 | 0.7844 |
| 0.0018 | 6.1503 | 2700 | 0.9177 | 0.8307 |
| 0.0007 | 6.3781 | 2800 | 1.1363 | 0.8003 |
| 0.001 | 6.6059 | 2900 | 0.9644 | 0.8274 |
| 0.0013 | 6.8337 | 3000 | 1.0775 | 0.8211 |
| 0.0027 | 7.0615 | 3100 | 1.4378 | 0.7627 |
| 0.0013 | 7.2893 | 3200 | 2.0668 | 0.7030 |
| 0.0038 | 7.5171 | 3300 | 1.9682 | 0.6941 |
| 0.0024 | 7.7449 | 3400 | 1.1606 | 0.7992 |
| 0.002 | 7.9727 | 3500 | 1.1364 | 0.8029 |
| 0.0002 | 8.2005 | 3600 | 1.0540 | 0.8185 |
| 0.0021 | 8.4282 | 3700 | 1.8765 | 0.7040 |
| 0.0003 | 8.6560 | 3800 | 1.3804 | 0.7721 |
| 0.0006 | 8.8838 | 3900 | 1.5498 | 0.7456 |
| 0.0011 | 9.1116 | 4000 | 1.4061 | 0.7703 |
| 0.0003 | 9.3394 | 4100 | 1.5528 | 0.7514 |
| 0.0013 | 9.5672 | 4200 | 1.5510 | 0.7585 |
| 0.0002 | 9.7950 | 4300 | 1.1179 | 0.8148 |
| 0.0001 | 10.0228 | 4400 | 1.5844 | 0.7557 |
| 0.001 | 10.2506 | 4500 | 1.2355 | 0.7990 |
| 0.0004 | 10.4784 | 4600 | 1.0223 | 0.8287 |
| 0.0009 | 10.7062 | 4700 | 1.7575 | 0.7332 |
| 0.0015 | 10.9339 | 4800 | 1.8685 | 0.7193 |
| 0.0007 | 11.1617 | 4900 | 1.2402 | 0.8015 |
| 0.0004 | 11.3895 | 5000 | 1.3765 | 0.7848 |
| 0.0003 | 11.6173 | 5100 | 1.6795 | 0.7471 |
| 0.0002 | 11.8451 | 5200 | 1.3439 | 0.7901 |
| 0.0007 | 12.0729 | 5300 | 2.0598 | 0.7095 |
| 0.0002 | 12.3007 | 5400 | 1.2197 | 0.8070 |
| 0.0001 | 12.5285 | 5500 | 1.1483 | 0.8127 |
| 0.0005 | 12.7563 | 5600 | 1.4303 | 0.7808 |
| 0.0005 | 12.9841 | 5700 | 1.2517 | 0.8017 |
| 0.0003 | 13.2118 | 5800 | 1.0473 | 0.8307 |
| 0.0005 | 13.4396 | 5900 | 1.3444 | 0.7816 |
| 0.0 | 13.6674 | 6000 | 1.2738 | 0.7930 |
| 0.0012 | 13.8952 | 6100 | 1.1715 | 0.8116 |
| 0.0003 | 14.1230 | 6200 | 1.4235 | 0.7794 |
| 0.0 | 14.3508 | 6300 | 1.4135 | 0.7815 |
| 0.0 | 14.5786 | 6400 | 1.4045 | 0.7830 |
| 0.0 | 14.8064 | 6500 | 1.4452 | 0.7787 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.1
- Datasets 2.19.2
- Tokenizers 0.19.1
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