beit-base-patch16-224-pt22k-ft22k-finetuned-conspiracy_imagery_2
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1099
- Accuracy: 0.5880
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.8533 | 0.9630 | 13 | 1.4568 | 0.4259 |
1.4844 | 2.0 | 27 | 1.2233 | 0.5417 |
1.1179 | 2.9630 | 40 | 1.1893 | 0.5509 |
1.0325 | 4.0 | 54 | 1.1467 | 0.5833 |
0.9755 | 4.9630 | 67 | 1.1300 | 0.5926 |
0.8969 | 5.7778 | 78 | 1.1099 | 0.5880 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for rvchi-schwenn/beit-base-patch16-224-pt22k-ft22k-finetuned-conspiracy_imagery_2
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k