---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-hate-meme
  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. -->

# vit-base-hate-meme

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the emily49/hateful_memes_train_dev dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7461
- Accuracy: 0.498

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6483        | 1.0   | 532  | 0.7933          | 0.5      |
| 0.6203        | 2.0   | 1064 | 0.7461          | 0.498    |
| 0.5955        | 3.0   | 1596 | 0.7539          | 0.518    |
| 0.4796        | 4.0   | 2128 | 0.9387          | 0.536    |
| 0.425         | 5.0   | 2660 | 0.9824          | 0.538    |
| 0.2869        | 6.0   | 3192 | 1.6186          | 0.542    |
| 0.0337        | 7.0   | 3724 | 2.5670          | 0.538    |
| 0.0166        | 8.0   | 4256 | 2.8061          | 0.538    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2