---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-meme-classifier
  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. -->

# bert-meme-classifier

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0546
- Accuracy: 0.46
- Auc: 0.636

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 1.0854        | 1.0   | 560  | 1.0647          | 0.43     | 0.619 |
| 1.0549        | 2.0   | 1120 | 1.0566          | 0.453    | 0.62  |
| 1.0372        | 3.0   | 1680 | 1.0591          | 0.421    | 0.627 |
| 1.0232        | 4.0   | 2240 | 1.0514          | 0.46     | 0.633 |
| 1.0203        | 5.0   | 2800 | 1.0655          | 0.439    | 0.634 |
| 1.0237        | 6.0   | 3360 | 1.0529          | 0.469    | 0.636 |
| 1.006         | 7.0   | 3920 | 1.0576          | 0.442    | 0.635 |
| 1.0035        | 8.0   | 4480 | 1.0529          | 0.444    | 0.637 |
| 0.9947        | 9.0   | 5040 | 1.0544          | 0.447    | 0.635 |
| 0.9897        | 10.0  | 5600 | 1.0546          | 0.46     | 0.636 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1