---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: elpv-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. -->

# elpv-vit

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7687
- Accuracy: 0.7259

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 69   | 1.1146          | 0.5787   |
| No log        | 2.0   | 138  | 0.9812          | 0.5787   |
| No log        | 3.0   | 207  | 0.8885          | 0.6472   |
| No log        | 4.0   | 276  | 0.7930          | 0.7081   |
| No log        | 5.0   | 345  | 0.8019          | 0.6929   |
| No log        | 6.0   | 414  | 0.8009          | 0.6878   |
| No log        | 7.0   | 483  | 0.7984          | 0.6853   |
| 0.8194        | 8.0   | 552  | 0.7714          | 0.7107   |
| 0.8194        | 9.0   | 621  | 0.7667          | 0.7081   |
| 0.8194        | 10.0  | 690  | 0.7303          | 0.7234   |
| 0.8194        | 11.0  | 759  | 0.7321          | 0.7284   |
| 0.8194        | 12.0  | 828  | 0.7373          | 0.7335   |
| 0.8194        | 13.0  | 897  | 0.8051          | 0.6904   |
| 0.8194        | 14.0  | 966  | 0.7687          | 0.7259   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0