activity_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: 0.7087
- Accuracy: 0.8012
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.7167 | 1.0 | 157 | 1.6188 | 0.6964 |
1.0511 | 2.0 | 315 | 1.0981 | 0.7381 |
0.9184 | 3.0 | 472 | 0.9225 | 0.7710 |
0.7396 | 4.0 | 630 | 0.8333 | 0.7802 |
0.6873 | 5.0 | 787 | 0.7917 | 0.7849 |
0.6579 | 6.0 | 945 | 0.7510 | 0.7845 |
0.5857 | 7.0 | 1102 | 0.7672 | 0.7845 |
0.4968 | 8.0 | 1260 | 0.7467 | 0.7857 |
0.513 | 9.0 | 1417 | 0.7156 | 0.7940 |
0.4957 | 9.97 | 1570 | 0.7073 | 0.8024 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Base model
google/vit-base-patch16-224-in21k