---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: my-roberta-for-hateful-meme-classification
  results: []
datasets:
- limjiayi/hateful_memes_expanded
---

<!-- 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. -->

# my-roberta-for-hateful-meme-classification

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an [hateful meme](https://huggingface.co/datasets/limjiayi/hateful_memes_expanded) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6894

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5181        | 1.0   | 806  | 0.7357          |
| 0.5235        | 2.0   | 1612 | 0.7480          |
| 0.4906        | 3.0   | 2418 | 0.7239          |
| 0.4673        | 4.0   | 3224 | 0.7252          |
| 0.4678        | 5.0   | 4030 | 0.6894          |
| 0.4481        | 6.0   | 4836 | 0.7794          |
| 0.4038        | 7.0   | 5642 | 0.7926          |
| 0.3052        | 8.0   | 6448 | 0.9150          |
| 0.2344        | 9.0   | 7254 | 1.1734          |
| 0.271         | 10.0  | 8060 | 1.1404          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1