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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
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