ViLT_Binary_Classifier_Abstract_Scenes
This model is a fine-tuned version of dandelin/vilt-b32-finetuned-vqa on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3099
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4285 | 0.08 | 100 | 1.4508 |
1.4158 | 0.17 | 200 | 1.6115 |
1.4004 | 0.25 | 300 | 1.3504 |
1.3907 | 0.34 | 400 | 1.3577 |
1.3568 | 0.42 | 500 | 1.3397 |
1.3562 | 0.5 | 600 | 1.3216 |
1.3566 | 0.59 | 700 | 1.3190 |
1.3255 | 0.67 | 800 | 1.3227 |
1.341 | 0.76 | 900 | 1.3411 |
1.3654 | 0.84 | 1000 | 1.3144 |
1.3343 | 0.92 | 1100 | 1.3099 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Base model
dandelin/vilt-b32-finetuned-vqa