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
