---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-hateful-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. -->

# distilbert-base-uncased-finetuned-hateful-meme

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8740
- Accuracy: 0.542

## 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: 2e-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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5786        | 1.0   | 532  | 0.7902          | 0.56     |
| 0.5077        | 2.0   | 1064 | 0.8275          | 0.566    |
| 0.4534        | 3.0   | 1596 | 0.9469          | 0.544    |
| 0.3998        | 4.0   | 2128 | 1.1139          | 0.538    |
| 0.3527        | 5.0   | 2660 | 1.2128          | 0.542    |
| 0.3219        | 6.0   | 3192 | 1.2232          | 0.546    |
| 0.3051        | 7.0   | 3724 | 1.5492          | 0.538    |
| 0.2789        | 8.0   | 4256 | 1.6341          | 0.542    |
| 0.267         | 9.0   | 4788 | 1.7046          | 0.54     |
| 0.2521        | 10.0  | 5320 | 1.8740          | 0.542    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3