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# dinov2-base-finetuned-har

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4424
- Accuracy: 0.8968

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9155        | 0.9910  | 83   | 0.6204          | 0.8053   |
| 0.749         | 1.9940  | 167  | 0.4433          | 0.8667   |
| 0.8197        | 2.9970  | 251  | 0.4826          | 0.8571   |
| 0.6854        | 4.0     | 335  | 0.4243          | 0.8725   |
| 0.7058        | 4.9910  | 418  | 0.4349          | 0.8593   |
| 0.6717        | 5.9940  | 502  | 0.4984          | 0.8434   |
| 0.6544        | 6.9970  | 586  | 0.4730          | 0.8545   |
| 0.5846        | 8.0     | 670  | 0.4631          | 0.8630   |
| 0.5207        | 8.9910  | 753  | 0.4072          | 0.8751   |
| 0.4977        | 9.9940  | 837  | 0.4627          | 0.8608   |
| 0.4974        | 10.9970 | 921  | 0.4600          | 0.8661   |
| 0.4502        | 12.0    | 1005 | 0.4548          | 0.8725   |
| 0.4051        | 12.9910 | 1088 | 0.4404          | 0.8709   |
| 0.3862        | 13.9940 | 1172 | 0.4498          | 0.8772   |
| 0.351         | 14.9970 | 1256 | 0.4859          | 0.8677   |
| 0.3807        | 16.0    | 1340 | 0.5189          | 0.8556   |
| 0.3538        | 16.9910 | 1423 | 0.4959          | 0.8646   |
| 0.3181        | 17.9940 | 1507 | 0.4831          | 0.8698   |
| 0.3225        | 18.9970 | 1591 | 0.4890          | 0.8804   |
| 0.3257        | 20.0    | 1675 | 0.4817          | 0.8735   |
| 0.2667        | 20.9910 | 1758 | 0.5199          | 0.8683   |
| 0.2863        | 21.9940 | 1842 | 0.4835          | 0.8683   |
| 0.2527        | 22.9970 | 1926 | 0.4764          | 0.8772   |
| 0.2657        | 24.0    | 2010 | 0.4651          | 0.8767   |
| 0.1995        | 24.9910 | 2093 | 0.5079          | 0.8693   |
| 0.2481        | 25.9940 | 2177 | 0.5112          | 0.8698   |
| 0.2072        | 26.9970 | 2261 | 0.5082          | 0.8831   |
| 0.2164        | 28.0    | 2345 | 0.5002          | 0.8730   |
| 0.2198        | 28.9910 | 2428 | 0.4785          | 0.8778   |
| 0.2137        | 29.9940 | 2512 | 0.5012          | 0.8889   |
| 0.1936        | 30.9970 | 2596 | 0.4961          | 0.8757   |
| 0.2255        | 32.0    | 2680 | 0.4987          | 0.8788   |
| 0.1818        | 32.9910 | 2763 | 0.4840          | 0.8852   |
| 0.1644        | 33.9940 | 2847 | 0.4694          | 0.8862   |
| 0.1799        | 34.9970 | 2931 | 0.4599          | 0.8915   |
| 0.1624        | 36.0    | 3015 | 0.5122          | 0.8852   |
| 0.157         | 36.9910 | 3098 | 0.4546          | 0.8899   |
| 0.2165        | 37.9940 | 3182 | 0.5097          | 0.8836   |
| 0.1565        | 38.9970 | 3266 | 0.4566          | 0.8952   |
| 0.1476        | 40.0    | 3350 | 0.4579          | 0.8915   |
| 0.1296        | 40.9910 | 3433 | 0.4595          | 0.8931   |
| 0.1159        | 41.9940 | 3517 | 0.4841          | 0.8884   |
| 0.1071        | 42.9970 | 3601 | 0.4730          | 0.8820   |
| 0.1017        | 44.0    | 3685 | 0.4470          | 0.8931   |
| 0.11          | 44.9910 | 3768 | 0.4557          | 0.8910   |
| 0.126         | 45.9940 | 3852 | 0.4585          | 0.8926   |
| 0.1079        | 46.9970 | 3936 | 0.4551          | 0.8905   |
| 0.1194        | 48.0    | 4020 | 0.4401          | 0.8947   |
| 0.11          | 48.9910 | 4103 | 0.4424          | 0.8968   |
| 0.1104        | 49.5522 | 4150 | 0.4414          | 0.8958   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

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