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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned-amazon
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. -->
# finetuned-amazon
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: 2.7690
- Accuracy: 0.1038
- F1: 0.0409
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.7793 | 0.27 | 100 | 2.7709 | 0.0390 | 0.0241 |
| 2.773 | 0.54 | 200 | 2.7767 | 0.0410 | 0.0230 |
| 2.7752 | 0.81 | 300 | 2.7872 | 0.0 | 0.0 |
| 2.7731 | 1.08 | 400 | 2.7793 | 0.0171 | 0.0111 |
| 2.7744 | 1.34 | 500 | 2.7733 | 0.0886 | 0.0507 |
| 2.7755 | 1.61 | 600 | 2.7740 | 0.0733 | 0.0376 |
| 2.7706 | 1.88 | 700 | 2.7755 | 0.0657 | 0.0401 |
| 2.7723 | 2.15 | 800 | 2.7690 | 0.1038 | 0.0409 |
| 2.7732 | 2.42 | 900 | 2.7738 | 0.1010 | 0.0410 |
| 2.7738 | 2.69 | 1000 | 2.7729 | 0.0914 | 0.0384 |
| 2.7734 | 2.96 | 1100 | 2.7732 | 0.0581 | 0.0343 |
| 2.7723 | 3.23 | 1200 | 2.7726 | 0.0638 | 0.0361 |
| 2.7725 | 3.49 | 1300 | 2.7731 | 0.0667 | 0.0297 |
| 2.7725 | 3.76 | 1400 | 2.7734 | 0.0476 | 0.0296 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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