transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: id1
  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. -->

# id1

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 sooks/id1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6181
- Accuracy: 0.6535

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.6933        | 0.53  | 10000  | 0.6932          | 0.5008   |
| 0.6933        | 1.06  | 20000  | 0.6933          | 0.4992   |
| 0.6933        | 1.59  | 30000  | 0.6931          | 0.5008   |
| 0.6933        | 2.12  | 40000  | 0.6931          | 0.5161   |
| 0.6931        | 2.65  | 50000  | 0.6933          | 0.4991   |
| 0.6932        | 3.19  | 60000  | 0.6932          | 0.4991   |
| 0.6746        | 3.72  | 70000  | 0.6725          | 0.5796   |
| 0.6582        | 4.25  | 80000  | 0.6614          | 0.6032   |
| 0.6455        | 4.78  | 90000  | 0.6466          | 0.6132   |
| 0.6256        | 5.31  | 100000 | 0.6325          | 0.6391   |
| 0.6144        | 5.84  | 110000 | 0.6181          | 0.6535   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
