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# mobileViTV2-128-2

This model is a fine-tuned version of [apple/mobilevitv2-1.0-imagenet1k-256](https://huggingface.co/apple/mobilevitv2-1.0-imagenet1k-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1494
- Accuracy: 0.9480
- F1: 0.9484
- Precision: 0.9498
- Recall: 0.9480

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.628         | 1.0   | 93   | 1.6205          | 0.1697   | 0.1607 | 0.1720    | 0.1697 |
| 1.6155        | 2.0   | 186  | 1.6120          | 0.2242   | 0.2119 | 0.2293    | 0.2242 |
| 1.6031        | 3.0   | 279  | 1.5941          | 0.2667   | 0.2650 | 0.2872    | 0.2667 |
| 1.5639        | 4.0   | 372  | 1.5756          | 0.3091   | 0.3022 | 0.3163    | 0.3091 |
| 1.525         | 5.0   | 465  | 1.5384          | 0.4      | 0.3949 | 0.4097    | 0.4    |
| 1.4892        | 6.0   | 558  | 1.4831          | 0.5091   | 0.4924 | 0.4945    | 0.5091 |
| 1.3605        | 7.0   | 651  | 1.3807          | 0.6      | 0.5801 | 0.5833    | 0.6    |
| 1.1423        | 8.0   | 744  | 1.2166          | 0.6242   | 0.5967 | 0.6139    | 0.6242 |
| 1.0801        | 9.0   | 837  | 1.0558          | 0.7030   | 0.6663 | 0.7190    | 0.7030 |
| 0.8504        | 10.0  | 930  | 0.8856          | 0.7697   | 0.7487 | 0.8081    | 0.7697 |
| 0.7659        | 11.0  | 1023 | 0.7253          | 0.8121   | 0.7954 | 0.8362    | 0.8121 |
| 0.547         | 12.0  | 1116 | 0.5812          | 0.8485   | 0.8418 | 0.8581    | 0.8485 |
| 0.5522        | 13.0  | 1209 | 0.4633          | 0.8970   | 0.8926 | 0.9078    | 0.8970 |
| 0.3583        | 14.0  | 1302 | 0.3797          | 0.9152   | 0.9119 | 0.9257    | 0.9152 |
| 0.3421        | 15.0  | 1395 | 0.3431          | 0.9273   | 0.9263 | 0.9379    | 0.9273 |
| 0.3624        | 16.0  | 1488 | 0.3010          | 0.9273   | 0.9265 | 0.9389    | 0.9273 |
| 0.2069        | 17.0  | 1581 | 0.2989          | 0.9152   | 0.9146 | 0.9260    | 0.9152 |
| 0.1639        | 18.0  | 1674 | 0.2797          | 0.9212   | 0.9205 | 0.9300    | 0.9212 |
| 0.2428        | 19.0  | 1767 | 0.2815          | 0.9273   | 0.9263 | 0.9379    | 0.9273 |
| 0.304         | 20.0  | 1860 | 0.2587          | 0.9333   | 0.9325 | 0.9432    | 0.9333 |
| 0.1349        | 21.0  | 1953 | 0.2617          | 0.9273   | 0.9266 | 0.9378    | 0.9273 |
| 0.2299        | 22.0  | 2046 | 0.2552          | 0.9333   | 0.9325 | 0.9432    | 0.9333 |
| 0.0894        | 23.0  | 2139 | 0.2560          | 0.9152   | 0.9149 | 0.9222    | 0.9152 |
| 0.1049        | 24.0  | 2232 | 0.2689          | 0.9152   | 0.9146 | 0.9226    | 0.9152 |
| 0.1201        | 25.0  | 2325 | 0.2921          | 0.9152   | 0.9144 | 0.9223    | 0.9152 |
| 0.1162        | 26.0  | 2418 | 0.3317          | 0.9212   | 0.9206 | 0.9283    | 0.9212 |
| 0.049         | 27.0  | 2511 | 0.2916          | 0.9273   | 0.9266 | 0.9346    | 0.9273 |
| 0.107         | 28.0  | 2604 | 0.2921          | 0.9273   | 0.9266 | 0.9346    | 0.9273 |
| 0.0521        | 29.0  | 2697 | 0.3267          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.1911        | 30.0  | 2790 | 0.3661          | 0.9091   | 0.9089 | 0.9147    | 0.9091 |
| 0.1636        | 31.0  | 2883 | 0.3444          | 0.9152   | 0.9147 | 0.9201    | 0.9152 |
| 0.0615        | 32.0  | 2976 | 0.3879          | 0.9212   | 0.9208 | 0.9277    | 0.9212 |
| 0.0581        | 33.0  | 3069 | 0.3606          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.1042        | 34.0  | 3162 | 0.3910          | 0.9333   | 0.9327 | 0.9404    | 0.9333 |
| 0.1468        | 35.0  | 3255 | 0.4503          | 0.9273   | 0.9266 | 0.9346    | 0.9273 |
| 0.0303        | 36.0  | 3348 | 0.4035          | 0.9152   | 0.9146 | 0.9207    | 0.9152 |
| 0.0512        | 37.0  | 3441 | 0.4157          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0627        | 38.0  | 3534 | 0.4399          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.091         | 39.0  | 3627 | 0.4023          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.1877        | 40.0  | 3720 | 0.4463          | 0.9152   | 0.9148 | 0.9187    | 0.9152 |
| 0.072         | 41.0  | 3813 | 0.4729          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0611        | 42.0  | 3906 | 0.5000          | 0.9152   | 0.9147 | 0.9201    | 0.9152 |
| 0.0308        | 43.0  | 3999 | 0.5051          | 0.9091   | 0.9087 | 0.9130    | 0.9091 |
| 0.0801        | 44.0  | 4092 | 0.5044          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0548        | 45.0  | 4185 | 0.5312          | 0.9212   | 0.9211 | 0.9259    | 0.9212 |
| 0.054         | 46.0  | 4278 | 0.5439          | 0.8970   | 0.8965 | 0.9031    | 0.8970 |
| 0.036         | 47.0  | 4371 | 0.5276          | 0.8970   | 0.8963 | 0.9027    | 0.8970 |
| 0.0172        | 48.0  | 4464 | 0.5379          | 0.8970   | 0.8966 | 0.9003    | 0.8970 |
| 0.0573        | 49.0  | 4557 | 0.5380          | 0.9152   | 0.9146 | 0.9207    | 0.9152 |
| 0.0593        | 50.0  | 4650 | 0.5323          | 0.9091   | 0.9089 | 0.9113    | 0.9091 |
| 0.073         | 51.0  | 4743 | 0.5931          | 0.9030   | 0.9029 | 0.9110    | 0.9030 |
| 0.0959        | 52.0  | 4836 | 0.5285          | 0.9152   | 0.9148 | 0.9187    | 0.9152 |
| 0.0251        | 53.0  | 4929 | 0.5081          | 0.9152   | 0.9150 | 0.9173    | 0.9152 |
| 0.0129        | 54.0  | 5022 | 0.5469          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0073        | 55.0  | 5115 | 0.5533          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0922        | 56.0  | 5208 | 0.5499          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0468        | 57.0  | 5301 | 0.5510          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0217        | 58.0  | 5394 | 0.5798          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0949        | 59.0  | 5487 | 0.5748          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0569        | 60.0  | 5580 | 0.5744          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0187        | 61.0  | 5673 | 0.5989          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0333        | 62.0  | 5766 | 0.6353          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.002         | 63.0  | 5859 | 0.6033          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0169        | 64.0  | 5952 | 0.6128          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0303        | 65.0  | 6045 | 0.6143          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0451        | 66.0  | 6138 | 0.6139          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0291        | 67.0  | 6231 | 0.6058          | 0.9152   | 0.9148 | 0.9187    | 0.9152 |
| 0.0163        | 68.0  | 6324 | 0.6154          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0181        | 69.0  | 6417 | 0.5810          | 0.9091   | 0.9089 | 0.9114    | 0.9091 |
| 0.0441        | 70.0  | 6510 | 0.6019          | 0.9152   | 0.9147 | 0.9203    | 0.9152 |
| 0.0395        | 71.0  | 6603 | 0.6018          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0229        | 72.0  | 6696 | 0.6280          | 0.9091   | 0.9084 | 0.9152    | 0.9091 |
| 0.0509        | 73.0  | 6789 | 0.6442          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0178        | 74.0  | 6882 | 0.6510          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0048        | 75.0  | 6975 | 0.6086          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0207        | 76.0  | 7068 | 0.6676          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0354        | 77.0  | 7161 | 0.6055          | 0.9152   | 0.9148 | 0.9187    | 0.9152 |
| 0.0233        | 78.0  | 7254 | 0.6043          | 0.9152   | 0.9150 | 0.9173    | 0.9152 |
| 0.0522        | 79.0  | 7347 | 0.6388          | 0.9152   | 0.9148 | 0.9187    | 0.9152 |
| 0.0519        | 80.0  | 7440 | 0.6531          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0129        | 81.0  | 7533 | 0.6346          | 0.9212   | 0.9209 | 0.9246    | 0.9212 |
| 0.0092        | 82.0  | 7626 | 0.6650          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0289        | 83.0  | 7719 | 0.6390          | 0.9091   | 0.9089 | 0.9114    | 0.9091 |
| 0.0561        | 84.0  | 7812 | 0.6260          | 0.9091   | 0.9090 | 0.9103    | 0.9091 |
| 0.063         | 85.0  | 7905 | 0.6484          | 0.9212   | 0.9207 | 0.9263    | 0.9212 |
| 0.0372        | 86.0  | 7998 | 0.6375          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0042        | 87.0  | 8091 | 0.6384          | 0.9152   | 0.9150 | 0.9173    | 0.9152 |
| 0.0659        | 88.0  | 8184 | 0.6734          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.016         | 89.0  | 8277 | 0.6275          | 0.9091   | 0.9089 | 0.9114    | 0.9091 |
| 0.0567        | 90.0  | 8370 | 0.6611          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0467        | 91.0  | 8463 | 0.6528          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0337        | 92.0  | 8556 | 0.6726          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0159        | 93.0  | 8649 | 0.6528          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.1206        | 94.0  | 8742 | 0.6997          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.051         | 95.0  | 8835 | 0.6729          | 0.9152   | 0.9150 | 0.9173    | 0.9152 |
| 0.0459        | 96.0  | 8928 | 0.6691          | 0.9212   | 0.9209 | 0.9246    | 0.9212 |
| 0.0338        | 97.0  | 9021 | 0.6332          | 0.9212   | 0.9207 | 0.9264    | 0.9212 |
| 0.0823        | 98.0  | 9114 | 0.6550          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |
| 0.0259        | 99.0  | 9207 | 0.6553          | 0.9212   | 0.9209 | 0.9246    | 0.9212 |
| 0.2724        | 100.0 | 9300 | 0.6473          | 0.9273   | 0.9268 | 0.9323    | 0.9273 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

durariadorio_128x128 mole_128x128 quebrado_128x128 riadorio_128x128 riofechado_128x128