---
library_name: transformers
license: apache-2.0
base_model: timm/resnet101.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/resnet101.a1_in1k](https://huggingface.co/timm/resnet101.a1_in1k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4913
- Accuracy: 0.8571

## 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: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.07          | 1.0   | 130  | 1.0683          | 0.4135   |
| 1.0523        | 2.0   | 260  | 1.0356          | 0.6241   |
| 1.0439        | 3.0   | 390  | 1.0045          | 0.6617   |
| 1.0056        | 4.0   | 520  | 0.9671          | 0.7293   |
| 0.9853        | 5.0   | 650  | 0.9245          | 0.7895   |
| 0.9581        | 6.0   | 780  | 0.8744          | 0.7820   |
| 0.9044        | 7.0   | 910  | 0.8172          | 0.7820   |
| 0.869         | 8.0   | 1040 | 0.7737          | 0.8271   |
| 0.8804        | 9.0   | 1170 | 0.7098          | 0.8271   |
| 0.7757        | 10.0  | 1300 | 0.6705          | 0.8120   |
| 0.7694        | 11.0  | 1430 | 0.6382          | 0.8571   |
| 0.7966        | 12.0  | 1560 | 0.6088          | 0.7895   |
| 0.7425        | 13.0  | 1690 | 0.5724          | 0.8496   |
| 0.7698        | 14.0  | 1820 | 0.5665          | 0.8195   |
| 0.6632        | 15.0  | 1950 | 0.5308          | 0.8571   |
| 0.6162        | 16.0  | 2080 | 0.5262          | 0.8346   |
| 0.6128        | 17.0  | 2210 | 0.5081          | 0.8421   |
| 0.685         | 18.0  | 2340 | 0.4913          | 0.8571   |
| 0.6614        | 19.0  | 2470 | 0.4937          | 0.8496   |
| 0.6934        | 20.0  | 2600 | 0.5027          | 0.8571   |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu118
- Datasets 2.21.0
- Tokenizers 0.20.0