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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-hate-meme |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-base-hate-meme |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7461 |
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- Accuracy: 0.498 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6483 | 1.0 | 532 | 0.7933 | 0.5 | |
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| 0.6203 | 2.0 | 1064 | 0.7461 | 0.498 | |
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| 0.5955 | 3.0 | 1596 | 0.7539 | 0.518 | |
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| 0.4796 | 4.0 | 2128 | 0.9387 | 0.536 | |
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| 0.425 | 5.0 | 2660 | 0.9824 | 0.538 | |
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| 0.2869 | 6.0 | 3192 | 1.6186 | 0.542 | |
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| 0.0337 | 7.0 | 3724 | 2.5670 | 0.538 | |
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| 0.0166 | 8.0 | 4256 | 2.8061 | 0.538 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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