---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beans_outputs
  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. -->

# beans_outputs

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the /home/ubuntu/sdb/astitva/segmentation/classification_ds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8746
- Accuracy: 0.9515

## 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: 42
- optimizer: Use OptimizerNames.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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1775        | 1.0   | 336  | 2.1821          | 0.7616   |
| 1.4653        | 2.0   | 672  | 1.4698          | 0.8840   |
| 1.1052        | 3.0   | 1008 | 1.0802          | 0.9304   |
| 1.0055        | 4.0   | 1344 | 0.9248          | 0.9494   |
| 0.7847        | 5.0   | 1680 | 0.8746          | 0.9515   |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0