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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
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 [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: 0.1114
- Accuracy: 0.9687
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6639 | 0.1829 | 100 | 0.6155 | 0.6554 |
| 0.4191 | 0.3657 | 200 | 0.3088 | 0.8959 |
| 0.1698 | 0.5486 | 300 | 0.5321 | 0.7281 |
| 0.0749 | 0.7314 | 400 | 0.5087 | 0.7900 |
| 0.0484 | 0.9143 | 500 | 0.4649 | 0.8185 |
| 0.0323 | 1.0971 | 600 | 0.6888 | 0.762 |
| 0.0264 | 1.28 | 700 | 0.1395 | 0.9513 |
| 0.0224 | 1.4629 | 800 | 0.0661 | 0.9776 |
| 0.02 | 1.6457 | 900 | 0.1173 | 0.9581 |
| 0.0168 | 1.8286 | 1000 | 0.3498 | 0.889 |
| 0.013 | 2.0114 | 1100 | 0.1053 | 0.9655 |
| 0.0087 | 2.1943 | 1200 | 0.3601 | 0.8947 |
| 0.0081 | 2.3771 | 1300 | 0.1508 | 0.9535 |
| 0.0073 | 2.56 | 1400 | 0.2090 | 0.9390 |
| 0.0056 | 2.7429 | 1500 | 0.1136 | 0.9649 |
| 0.005 | 2.9257 | 1600 | 0.2656 | 0.9206 |
| 0.0036 | 3.1086 | 1700 | 0.1320 | 0.9595 |
| 0.002 | 3.2914 | 1800 | 0.1068 | 0.9686 |
| 0.0018 | 3.4743 | 1900 | 0.1091 | 0.9690 |
| 0.0019 | 3.6571 | 2000 | 0.1114 | 0.9687 |
| 0.0018 | 3.84 | 2100 | 0.0968 | 0.9719 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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