metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: finetuned-fer2013-balanced
results: []
finetuned-fer2013-balanced
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0183
- Accuracy: 0.6362
- Precision: 0.6312
- Recall: 0.6362
- F1: 0.6310
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 17
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.3969 | 1.0 | 267 | 1.3735 | 0.4996 | 0.4776 | 0.4996 | 0.4436 |
| 1.2341 | 2.0 | 534 | 1.2239 | 0.5442 | 0.5430 | 0.5442 | 0.5108 |
| 1.1363 | 3.0 | 801 | 1.1585 | 0.5758 | 0.5715 | 0.5758 | 0.5638 |
| 1.0894 | 4.0 | 1068 | 1.1087 | 0.5912 | 0.5827 | 0.5912 | 0.5706 |
| 1.0666 | 5.0 | 1335 | 1.0655 | 0.6184 | 0.6111 | 0.6184 | 0.6082 |
| 0.9219 | 6.0 | 1602 | 1.0520 | 0.6233 | 0.6153 | 0.6233 | 0.6136 |
| 0.943 | 7.0 | 1869 | 1.0331 | 0.6299 | 0.6238 | 0.6299 | 0.6231 |
| 0.8906 | 8.0 | 2136 | 1.0238 | 0.6318 | 0.6252 | 0.6318 | 0.6239 |
| 0.8854 | 9.0 | 2403 | 1.0196 | 0.6341 | 0.6313 | 0.6341 | 0.6298 |
| 0.8991 | 10.0 | 2670 | 1.0183 | 0.6362 | 0.6312 | 0.6362 | 0.6310 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2