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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: 0.7631
- Accuracy: 0.7710
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1235 | 1.0 | 315 | 1.3182 | 0.7099 |
| 1.0404 | 2.0 | 630 | 0.9831 | 0.7278 |
| 0.7899 | 3.0 | 945 | 0.9509 | 0.7175 |
| 0.6961 | 4.0 | 1260 | 0.8258 | 0.7460 |
| 0.615 | 5.0 | 1575 | 0.7890 | 0.7667 |
| 0.5534 | 6.0 | 1890 | 0.7876 | 0.7591 |
| 0.524 | 7.0 | 2205 | 0.7627 | 0.7663 |
| 0.4588 | 8.0 | 2520 | 0.8256 | 0.7468 |
| 0.4407 | 9.0 | 2835 | 0.8041 | 0.7615 |
| 0.4039 | 10.0 | 3150 | 0.8367 | 0.7540 |
| 0.3966 | 11.0 | 3465 | 0.8708 | 0.7492 |
| 0.366 | 12.0 | 3780 | 0.8410 | 0.7544 |
| 0.3522 | 13.0 | 4095 | 0.9019 | 0.7365 |
| 0.3495 | 14.0 | 4410 | 0.8240 | 0.7567 |
| 0.3206 | 15.0 | 4725 | 0.8428 | 0.7607 |
| 0.3172 | 16.0 | 5040 | 0.8626 | 0.7607 |
| 0.2931 | 17.0 | 5355 | 1.0311 | 0.7306 |
| 0.2943 | 18.0 | 5670 | 0.9393 | 0.7544 |
| 0.2886 | 19.0 | 5985 | 0.9379 | 0.7472 |
| 0.2785 | 20.0 | 6300 | 0.8911 | 0.7552 |
| 0.274 | 21.0 | 6615 | 0.9730 | 0.7484 |
| 0.2716 | 22.0 | 6930 | 0.9546 | 0.7504 |
| 0.2686 | 23.0 | 7245 | 0.8939 | 0.7651 |
| 0.2489 | 24.0 | 7560 | 0.9397 | 0.7480 |
| 0.257 | 25.0 | 7875 | 0.9298 | 0.7552 |
| 0.244 | 26.0 | 8190 | 0.9977 | 0.7437 |
| 0.2333 | 27.0 | 8505 | 0.9967 | 0.75 |
| 0.2376 | 28.0 | 8820 | 1.0012 | 0.7508 |
| 0.2428 | 29.0 | 9135 | 0.9674 | 0.7421 |
| 0.224 | 30.0 | 9450 | 1.0239 | 0.7361 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
