|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224 |
|
tags: |
|
- image-classification |
|
- generated_from_trainer |
|
model-index: |
|
- name: vit-base-hate-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. --> |
|
|
|
# vit-base-hate-meme |
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the emily49/hateful_memes_train_dev dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6966 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 32 |
|
- 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: 8 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.6407 | 1.0 | 532 | 0.6966 | |
|
| 0.5847 | 2.0 | 1064 | 0.7980 | |
|
| 0.6144 | 3.0 | 1596 | 0.7764 | |
|
| 0.5307 | 4.0 | 2128 | 0.9913 | |
|
| 0.5545 | 5.0 | 2660 | 0.9512 | |
|
| 0.3243 | 6.0 | 3192 | 1.5071 | |
|
| 0.1371 | 7.0 | 3724 | 2.0203 | |
|
| 0.0571 | 8.0 | 4256 | 2.9499 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
