---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lens-2
  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. -->

# lens-2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5324
- Accuracy: 0.545

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0399        | 1.0   | 100  | 2.1707          | 0.52     |
| 0.069         | 2.0   | 200  | 2.2835          | 0.52     |
| 0.0631        | 3.0   | 300  | 2.5655          | 0.5      |
| 0.0667        | 4.0   | 400  | 2.1765          | 0.55     |
| 0.0055        | 5.0   | 500  | 2.4217          | 0.535    |
| 0.0087        | 6.0   | 600  | 2.3678          | 0.545    |
| 0.0492        | 7.0   | 700  | 2.4301          | 0.535    |
| 0.0049        | 8.0   | 800  | 2.3669          | 0.545    |
| 0.0091        | 9.0   | 900  | 2.5554          | 0.5      |
| 0.016         | 10.0  | 1000 | 2.4330          | 0.545    |
| 0.0345        | 11.0  | 1100 | 2.3653          | 0.575    |
| 0.1143        | 12.0  | 1200 | 2.5124          | 0.54     |
| 0.2871        | 13.0  | 1300 | 2.3495          | 0.555    |
| 0.1154        | 14.0  | 1400 | 2.2519          | 0.56     |
| 0.1388        | 15.0  | 1500 | 2.4013          | 0.54     |
| 0.1445        | 16.0  | 1600 | 2.3764          | 0.535    |
| 0.1094        | 17.0  | 1700 | 2.5227          | 0.5      |
| 0.0884        | 18.0  | 1800 | 2.4164          | 0.55     |
| 0.156         | 19.0  | 1900 | 2.4202          | 0.555    |
| 0.0055        | 20.0  | 2000 | 2.5324          | 0.545    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1