metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Emotion_Classification
results: []
Emotion_Classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3727
- Accuracy: 0.55
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.083 | 1.0 | 10 | 2.0798 | 0.1625 |
| 2.0591 | 2.0 | 20 | 2.0464 | 0.2812 |
| 2.0043 | 3.0 | 30 | 1.9889 | 0.325 |
| 1.9174 | 4.0 | 40 | 1.9087 | 0.3375 |
| 1.819 | 5.0 | 50 | 1.8037 | 0.3875 |
| 1.7161 | 6.0 | 60 | 1.6875 | 0.4125 |
| 1.6253 | 7.0 | 70 | 1.6207 | 0.4437 |
| 1.549 | 8.0 | 80 | 1.5978 | 0.4437 |
| 1.4946 | 9.0 | 90 | 1.5430 | 0.4688 |
| 1.4426 | 10.0 | 100 | 1.4995 | 0.5125 |
| 1.4061 | 11.0 | 110 | 1.4919 | 0.4938 |
| 1.3648 | 12.0 | 120 | 1.4628 | 0.525 |
| 1.3306 | 13.0 | 130 | 1.4207 | 0.5437 |
| 1.3071 | 14.0 | 140 | 1.4340 | 0.5188 |
| 1.2791 | 15.0 | 150 | 1.4126 | 0.5188 |
| 1.2589 | 16.0 | 160 | 1.4119 | 0.5375 |
| 1.2199 | 17.0 | 170 | 1.4168 | 0.4938 |
| 1.2189 | 18.0 | 180 | 1.3957 | 0.525 |
| 1.2096 | 19.0 | 190 | 1.4015 | 0.5625 |
| 1.2114 | 20.0 | 200 | 1.3932 | 0.5188 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3