---
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