---
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: plant-identification-vit
  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. -->

# plant-identification-vit

This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0315
- Accuracy: 0.8096

## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0085        | 1.0   | 953  | 1.0659          | 0.7762   |
| 0.6805        | 2.0   | 1906 | 0.8413          | 0.8029   |
| 0.5039        | 3.0   | 2859 | 0.7920          | 0.8069   |
| 0.3847        | 4.0   | 3812 | 0.7760          | 0.8102   |
| 0.2826        | 5.0   | 4765 | 0.8024          | 0.8049   |
| 0.2229        | 6.0   | 5718 | 0.8382          | 0.8099   |
| 0.1064        | 7.0   | 6671 | 0.8983          | 0.8074   |
| 0.0676        | 8.0   | 7624 | 0.9672          | 0.8072   |
| 0.027         | 9.0   | 8577 | 1.0089          | 0.8099   |
| 0.0209        | 10.0  | 9530 | 1.0315          | 0.8096   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3