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# ebayes/tree_crown_model-test23

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2838
- Accuracy: 0.8696

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 11   | 1.9719          | 0.6522   |
| No log        | 2.0   | 22   | 1.6381          | 0.6522   |
| No log        | 3.0   | 33   | 1.3958          | 0.6522   |
| No log        | 4.0   | 44   | 1.2541          | 0.6522   |
| No log        | 5.0   | 55   | 1.1207          | 0.6957   |
| No log        | 6.0   | 66   | 1.0262          | 0.8261   |
| No log        | 7.0   | 77   | 0.9421          | 0.8261   |
| No log        | 8.0   | 88   | 0.9031          | 0.8261   |
| No log        | 9.0   | 99   | 0.8398          | 0.8261   |
| No log        | 10.0  | 110  | 0.7975          | 0.8261   |
| No log        | 11.0  | 121  | 0.7547          | 0.8696   |
| No log        | 12.0  | 132  | 0.7451          | 0.8696   |
| No log        | 13.0  | 143  | 0.7017          | 0.8696   |
| No log        | 14.0  | 154  | 0.6789          | 0.8696   |
| No log        | 15.0  | 165  | 0.6688          | 0.8696   |
| No log        | 16.0  | 176  | 0.6809          | 0.8696   |
| No log        | 17.0  | 187  | 0.6342          | 0.8696   |
| No log        | 18.0  | 198  | 0.6437          | 0.8696   |
| No log        | 19.0  | 209  | 0.5902          | 0.8696   |
| No log        | 20.0  | 220  | 0.5874          | 0.8696   |
| No log        | 21.0  | 231  | 0.6042          | 0.8696   |
| No log        | 22.0  | 242  | 0.5682          | 0.8696   |
| No log        | 23.0  | 253  | 0.5395          | 0.8696   |
| No log        | 24.0  | 264  | 0.5487          | 0.8696   |
| No log        | 25.0  | 275  | 0.5239          | 0.8696   |
| No log        | 26.0  | 286  | 0.5436          | 0.8696   |
| No log        | 27.0  | 297  | 0.5169          | 0.8696   |
| No log        | 28.0  | 308  | 0.5189          | 0.8696   |
| No log        | 29.0  | 319  | 0.5314          | 0.8261   |
| No log        | 30.0  | 330  | 0.4707          | 0.8696   |
| No log        | 31.0  | 341  | 0.5169          | 0.8261   |
| No log        | 32.0  | 352  | 0.5229          | 0.8696   |
| No log        | 33.0  | 363  | 0.4598          | 0.8696   |
| No log        | 34.0  | 374  | 0.4911          | 0.8696   |
| No log        | 35.0  | 385  | 0.4516          | 0.8696   |
| No log        | 36.0  | 396  | 0.4121          | 0.9130   |
| No log        | 37.0  | 407  | 0.4875          | 0.8696   |
| No log        | 38.0  | 418  | 0.4147          | 0.9130   |
| No log        | 39.0  | 429  | 0.5118          | 0.8696   |
| No log        | 40.0  | 440  | 0.4266          | 0.8696   |
| No log        | 41.0  | 451  | 0.4114          | 0.8696   |
| No log        | 42.0  | 462  | 0.4549          | 0.8261   |
| No log        | 43.0  | 473  | 0.3795          | 0.9565   |
| No log        | 44.0  | 484  | 0.4286          | 0.8696   |
| No log        | 45.0  | 495  | 0.4409          | 0.8696   |
| 0.6437        | 46.0  | 506  | 0.4099          | 0.8696   |
| 0.6437        | 47.0  | 517  | 0.4075          | 0.9130   |
| 0.6437        | 48.0  | 528  | 0.3886          | 0.9130   |
| 0.6437        | 49.0  | 539  | 0.3900          | 0.8696   |
| 0.6437        | 50.0  | 550  | 0.3947          | 0.8696   |
| 0.6437        | 51.0  | 561  | 0.3676          | 0.8696   |
| 0.6437        | 52.0  | 572  | 0.3560          | 0.9130   |
| 0.6437        | 53.0  | 583  | 0.4100          | 0.8696   |
| 0.6437        | 54.0  | 594  | 0.4078          | 0.8696   |
| 0.6437        | 55.0  | 605  | 0.4357          | 0.8696   |
| 0.6437        | 56.0  | 616  | 0.3815          | 0.8696   |
| 0.6437        | 57.0  | 627  | 0.4172          | 0.8696   |
| 0.6437        | 58.0  | 638  | 0.4781          | 0.8696   |
| 0.6437        | 59.0  | 649  | 0.3847          | 0.8696   |
| 0.6437        | 60.0  | 660  | 0.3260          | 0.9130   |
| 0.6437        | 61.0  | 671  | 0.3578          | 0.8696   |
| 0.6437        | 62.0  | 682  | 0.3096          | 0.9130   |
| 0.6437        | 63.0  | 693  | 0.2946          | 0.9130   |
| 0.6437        | 64.0  | 704  | 0.3383          | 0.8696   |
| 0.6437        | 65.0  | 715  | 0.3748          | 0.8696   |
| 0.6437        | 66.0  | 726  | 0.3199          | 0.9130   |
| 0.6437        | 67.0  | 737  | 0.3761          | 0.8696   |
| 0.6437        | 68.0  | 748  | 0.3332          | 0.8696   |
| 0.6437        | 69.0  | 759  | 0.2815          | 0.9130   |
| 0.6437        | 70.0  | 770  | 0.3236          | 0.8696   |
| 0.6437        | 71.0  | 781  | 0.2962          | 0.9130   |
| 0.6437        | 72.0  | 792  | 0.3075          | 0.9130   |
| 0.6437        | 73.0  | 803  | 0.3461          | 0.8696   |
| 0.6437        | 74.0  | 814  | 0.3138          | 0.9130   |
| 0.6437        | 75.0  | 825  | 0.3043          | 0.9130   |
| 0.6437        | 76.0  | 836  | 0.2967          | 0.9130   |
| 0.6437        | 77.0  | 847  | 0.3008          | 0.9130   |
| 0.6437        | 78.0  | 858  | 0.2856          | 0.9130   |
| 0.6437        | 79.0  | 869  | 0.2939          | 0.9130   |
| 0.6437        | 80.0  | 880  | 0.3491          | 0.9130   |
| 0.6437        | 81.0  | 891  | 0.3049          | 0.9130   |
| 0.6437        | 82.0  | 902  | 0.3577          | 0.8696   |
| 0.6437        | 83.0  | 913  | 0.3369          | 0.8696   |
| 0.6437        | 84.0  | 924  | 0.2952          | 0.9130   |
| 0.6437        | 85.0  | 935  | 0.2881          | 0.9130   |
| 0.6437        | 86.0  | 946  | 0.3349          | 0.8696   |
| 0.6437        | 87.0  | 957  | 0.3025          | 0.9130   |
| 0.6437        | 88.0  | 968  | 0.2943          | 0.8696   |
| 0.6437        | 89.0  | 979  | 0.3035          | 0.9130   |
| 0.6437        | 90.0  | 990  | 0.2599          | 0.9130   |
| 0.1677        | 91.0  | 1001 | 0.3061          | 0.8696   |
| 0.1677        | 92.0  | 1012 | 0.4316          | 0.8261   |
| 0.1677        | 93.0  | 1023 | 0.3431          | 0.8696   |
| 0.1677        | 94.0  | 1034 | 0.3246          | 0.8696   |
| 0.1677        | 95.0  | 1045 | 0.3256          | 0.8696   |
| 0.1677        | 96.0  | 1056 | 0.2846          | 0.9130   |
| 0.1677        | 97.0  | 1067 | 0.3077          | 0.8696   |
| 0.1677        | 98.0  | 1078 | 0.2988          | 0.9130   |
| 0.1677        | 99.0  | 1089 | 0.2957          | 0.9130   |
| 0.1677        | 100.0 | 1100 | 0.2983          | 0.9130   |
| 0.1677        | 101.0 | 1111 | 0.2908          | 0.8696   |
| 0.1677        | 102.0 | 1122 | 0.2715          | 0.9130   |
| 0.1677        | 103.0 | 1133 | 0.3208          | 0.9130   |
| 0.1677        | 104.0 | 1144 | 0.3622          | 0.8261   |
| 0.1677        | 105.0 | 1155 | 0.3314          | 0.8696   |
| 0.1677        | 106.0 | 1166 | 0.3226          | 0.9130   |
| 0.1677        | 107.0 | 1177 | 0.3009          | 0.9565   |
| 0.1677        | 108.0 | 1188 | 0.3162          | 0.9130   |
| 0.1677        | 109.0 | 1199 | 0.2927          | 0.9565   |
| 0.1677        | 110.0 | 1210 | 0.2434          | 0.9130   |
| 0.1677        | 111.0 | 1221 | 0.3389          | 0.8696   |
| 0.1677        | 112.0 | 1232 | 0.3686          | 0.8696   |
| 0.1677        | 113.0 | 1243 | 0.3192          | 0.9130   |
| 0.1677        | 114.0 | 1254 | 0.2720          | 0.8696   |
| 0.1677        | 115.0 | 1265 | 0.2955          | 0.8696   |
| 0.1677        | 116.0 | 1276 | 0.3318          | 0.9130   |
| 0.1677        | 117.0 | 1287 | 0.3248          | 0.9130   |
| 0.1677        | 118.0 | 1298 | 0.3115          | 0.8696   |
| 0.1677        | 119.0 | 1309 | 0.2711          | 0.9130   |
| 0.1677        | 120.0 | 1320 | 0.2592          | 0.8696   |
| 0.1677        | 121.0 | 1331 | 0.2830          | 0.8696   |
| 0.1677        | 122.0 | 1342 | 0.2956          | 0.9130   |
| 0.1677        | 123.0 | 1353 | 0.3158          | 0.9130   |
| 0.1677        | 124.0 | 1364 | 0.3328          | 0.8696   |
| 0.1677        | 125.0 | 1375 | 0.3487          | 0.8696   |
| 0.1677        | 126.0 | 1386 | 0.3375          | 0.8696   |
| 0.1677        | 127.0 | 1397 | 0.3488          | 0.8696   |
| 0.1677        | 128.0 | 1408 | 0.3377          | 0.8696   |
| 0.1677        | 129.0 | 1419 | 0.3295          | 0.8696   |
| 0.1677        | 130.0 | 1430 | 0.3198          | 0.8696   |
| 0.1677        | 131.0 | 1441 | 0.2813          | 0.9130   |
| 0.1677        | 132.0 | 1452 | 0.2730          | 0.9130   |
| 0.1677        | 133.0 | 1463 | 0.2861          | 0.8696   |
| 0.1677        | 134.0 | 1474 | 0.3158          | 0.8696   |
| 0.1677        | 135.0 | 1485 | 0.3229          | 0.8696   |
| 0.1677        | 136.0 | 1496 | 0.3169          | 0.8696   |
| 0.1074        | 137.0 | 1507 | 0.3215          | 0.8696   |
| 0.1074        | 138.0 | 1518 | 0.3039          | 0.8696   |
| 0.1074        | 139.0 | 1529 | 0.2803          | 0.9130   |
| 0.1074        | 140.0 | 1540 | 0.2707          | 0.9130   |
| 0.1074        | 141.0 | 1551 | 0.2601          | 0.9130   |
| 0.1074        | 142.0 | 1562 | 0.2599          | 0.9130   |
| 0.1074        | 143.0 | 1573 | 0.2647          | 0.9130   |
| 0.1074        | 144.0 | 1584 | 0.2697          | 0.9130   |
| 0.1074        | 145.0 | 1595 | 0.2738          | 0.9130   |
| 0.1074        | 146.0 | 1606 | 0.2759          | 0.9130   |
| 0.1074        | 147.0 | 1617 | 0.2797          | 0.9130   |
| 0.1074        | 148.0 | 1628 | 0.2798          | 0.9130   |
| 0.1074        | 149.0 | 1639 | 0.2829          | 0.8696   |
| 0.1074        | 150.0 | 1650 | 0.2838          | 0.8696   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

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