---
library_name: transformers
license: apache-2.0
base_model: timm/resnet18.a1_in1k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans
  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-beans

This model is a fine-tuned version of [timm/resnet18.a1_in1k](https://huggingface.co/timm/resnet18.a1_in1k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8550
- Accuracy: 0.7895

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.0881        | 1.0   | 130  | 0.4135   | 1.0902          |
| 1.0716        | 2.0   | 260  | 0.5038   | 1.0685          |
| 1.061         | 3.0   | 390  | 0.6241   | 1.0459          |
| 1.0514        | 4.0   | 520  | 0.6015   | 1.0407          |
| 1.05          | 5.0   | 650  | 0.6767   | 1.0332          |
| 1.0357        | 6.0   | 780  | 1.0109   | 0.6541          |
| 1.0012        | 7.0   | 910  | 0.9815   | 0.7368          |
| 0.9932        | 8.0   | 1040 | 0.9550   | 0.7669          |
| 0.9748        | 9.0   | 1170 | 0.9409   | 0.7669          |
| 0.9113        | 10.0  | 1300 | 0.9149   | 0.7820          |
| 0.9255        | 11.0  | 1430 | 0.8906   | 0.7895          |
| 0.8877        | 12.0  | 1560 | 0.8749   | 0.7895          |
| 0.9032        | 13.0  | 1690 | 0.8699   | 0.7970          |
| 0.9001        | 14.0  | 1820 | 0.8674   | 0.7820          |
| 0.8842        | 15.0  | 1950 | 0.8550   | 0.7895          |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu118
- Datasets 2.21.0
- Tokenizers 0.20.0