Louis_Emotion_DF_Image_VIT_V2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.9591
- Accuracy: 0.6776
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.148 | 1.0 | 1795 | 1.1148 | 0.5982 |
0.8387 | 2.0 | 3590 | 1.0005 | 0.6411 |
0.8989 | 3.0 | 5385 | 0.9685 | 0.6486 |
0.8048 | 4.0 | 7180 | 0.9354 | 0.6559 |
0.6871 | 5.0 | 8975 | 0.9494 | 0.6559 |
0.5955 | 6.0 | 10770 | 0.9346 | 0.6693 |
0.472 | 7.0 | 12565 | 0.9493 | 0.6746 |
0.4086 | 8.0 | 14360 | 0.9603 | 0.6776 |
0.3915 | 9.0 | 16155 | 0.9929 | 0.6773 |
0.3441 | 10.0 | 17950 | 1.0307 | 0.6760 |
0.3019 | 11.0 | 19745 | 1.0561 | 0.6768 |
0.3528 | 12.0 | 21540 | 1.0845 | 0.6743 |
0.1964 | 13.0 | 23335 | 1.1124 | 0.6734 |
0.3125 | 14.0 | 25130 | 1.1289 | 0.6734 |
0.1854 | 15.0 | 26925 | 1.1372 | 0.6704 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
google/vit-base-patch16-224-in21k