---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-hateful-meme-restructured-balanced
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.522
---

<!-- 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. -->

# resnet-50-finetuned-hateful-meme-restructured-balanced

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6946
- Accuracy: 0.522

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6941        | 0.98  | 47   | 0.6947          | 0.494    |
| 0.6906        | 1.99  | 95   | 0.6945          | 0.492    |
| 0.6885        | 2.99  | 143  | 0.6951          | 0.492    |
| 0.6873        | 4.0   | 191  | 0.6946          | 0.5      |
| 0.6851        | 4.98  | 238  | 0.6941          | 0.516    |
| 0.6813        | 5.99  | 286  | 0.6946          | 0.522    |
| 0.6817        | 6.99  | 334  | 0.6955          | 0.508    |
| 0.6849        | 8.0   | 382  | 0.6948          | 0.52     |
| 0.6834        | 8.98  | 429  | 0.6953          | 0.508    |
| 0.6758        | 9.84  | 470  | 0.6953          | 0.516    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3