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vit-base-blur
This model is a fine-tuned version of WT-MM/vit-base-blur on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 2.2932
- Accuracy: 0.5333
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8 | 1 | 3.1867 | 0.4667 |
| No log | 1.6 | 2 | 2.2932 | 0.5333 |
| No log | 2.4 | 3 | 2.9066 | 0.5333 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
