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emotion_classification
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: 1.2745
- Accuracy: 0.6375
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 20 | 1.7629 | 0.4375 |
| No log | 2.0 | 40 | 1.5012 | 0.5 |
| No log | 3.0 | 60 | 1.3757 | 0.5 |
| No log | 4.0 | 80 | 1.2452 | 0.5625 |
| No log | 5.0 | 100 | 1.2394 | 0.5625 |
| No log | 6.0 | 120 | 1.2083 | 0.6125 |
| No log | 7.0 | 140 | 1.2209 | 0.575 |
| No log | 8.0 | 160 | 1.2755 | 0.5875 |
| No log | 9.0 | 180 | 1.2794 | 0.5687 |
| No log | 10.0 | 200 | 1.2639 | 0.6125 |
| No log | 11.0 | 220 | 1.3129 | 0.6125 |
| No log | 12.0 | 240 | 1.2277 | 0.6312 |
| No log | 13.0 | 260 | 1.3620 | 0.5938 |
| No log | 14.0 | 280 | 1.3023 | 0.6062 |
| No log | 15.0 | 300 | 1.3334 | 0.6 |
| No log | 16.0 | 320 | 1.4142 | 0.5813 |
| No log | 17.0 | 340 | 1.2863 | 0.6125 |
| No log | 18.0 | 360 | 1.4084 | 0.5875 |
| No log | 19.0 | 380 | 1.4195 | 0.575 |
| No log | 20.0 | 400 | 1.4164 | 0.5938 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
