
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-cocoa

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the SemilleroCV/Cocoa-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2061
- Accuracy: 0.9278

## 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: 8
- eval_batch_size: 8
- seed: 1337
- 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
- num_epochs: 100.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.3733        | 1.0   | 196   | 0.9025   | 0.3558          |
| 0.3727        | 2.0   | 392   | 0.8989   | 0.4098          |
| 0.3901        | 3.0   | 588   | 0.8989   | 0.2668          |
| 0.3421        | 4.0   | 784   | 0.9170   | 0.2612          |
| 0.2703        | 5.0   | 980   | 0.9278   | 0.2061          |
| 0.1734        | 6.0   | 1176  | 0.9278   | 0.2568          |
| 0.1385        | 7.0   | 1372  | 0.9206   | 0.3242          |
| 0.3237        | 8.0   | 1568  | 0.9386   | 0.2922          |
| 0.236         | 9.0   | 1764  | 0.9386   | 0.3044          |
| 0.2124        | 10.0  | 1960  | 0.9061   | 0.3848          |
| 0.0454        | 11.0  | 2156  | 0.9350   | 0.3527          |
| 0.0756        | 12.0  | 2352  | 0.9350   | 0.2844          |
| 0.0605        | 13.0  | 2548  | 0.9314   | 0.3077          |
| 0.0214        | 14.0  | 2744  | 0.9025   | 0.6295          |
| 0.1816        | 15.0  | 2940  | 0.9386   | 0.2996          |
| 0.0338        | 16.0  | 3136  | 0.9278   | 0.3597          |
| 0.2136        | 17.0  | 3332  | 0.9314   | 0.4070          |
| 0.188         | 18.0  | 3528  | 0.9458   | 0.3532          |
| 0.0539        | 19.0  | 3724  | 0.9386   | 0.3843          |
| 0.0992        | 20.0  | 3920  | 0.9422   | 0.3904          |
| 0.0019        | 21.0  | 4116  | 0.9458   | 0.3732          |
| 0.0348        | 22.0  | 4312  | 0.9386   | 0.4021          |
| 0.0823        | 23.0  | 4508  | 0.9350   | 0.4217          |
| 0.1125        | 24.0  | 4704  | 0.9097   | 0.4704          |
| 0.0173        | 25.0  | 4900  | 0.9350   | 0.3700          |
| 0.0442        | 26.0  | 5096  | 0.9314   | 0.3725          |
| 0.0009        | 27.0  | 5292  | 0.9278   | 0.4819          |
| 0.0087        | 28.0  | 5488  | 0.9170   | 0.6492          |
| 0.0021        | 29.0  | 5684  | 0.9242   | 0.5297          |
| 0.2552        | 30.0  | 5880  | 0.9314   | 0.4482          |
| 0.0154        | 31.0  | 6076  | 0.9242   | 0.6075          |
| 0.0009        | 32.0  | 6272  | 0.9350   | 0.4101          |
| 0.1626        | 33.0  | 6468  | 0.9350   | 0.4653          |
| 0.0276        | 34.0  | 6664  | 0.9386   | 0.4174          |
| 0.0139        | 35.0  | 6860  | 0.9422   | 0.3992          |
| 0.0023        | 36.0  | 7056  | 0.9170   | 0.6972          |
| 0.1264        | 37.0  | 7252  | 0.9314   | 0.4980          |
| 0.0113        | 38.0  | 7448  | 0.9170   | 0.7154          |
| 0.0694        | 39.0  | 7644  | 0.9242   | 0.5443          |
| 0.0976        | 40.0  | 7840  | 0.9350   | 0.3852          |
| 0.1191        | 41.0  | 8036  | 0.9242   | 0.5398          |
| 0.1249        | 42.0  | 8232  | 0.9170   | 0.6197          |
| 0.0002        | 43.0  | 8428  | 0.9134   | 0.6967          |
| 0.1163        | 44.0  | 8624  | 0.9242   | 0.5697          |
| 0.0201        | 45.0  | 8820  | 0.9134   | 0.7221          |
| 0.0003        | 46.0  | 9016  | 0.9314   | 0.5253          |
| 0.0224        | 47.0  | 9212  | 0.9495   | 0.3817          |
| 0.0183        | 48.0  | 9408  | 0.9242   | 0.4966          |
| 0.0077        | 49.0  | 9604  | 0.9458   | 0.4349          |
| 0.0083        | 50.0  | 9800  | 0.9242   | 0.5191          |
| 0.0571        | 51.0  | 9996  | 0.9206   | 0.5826          |
| 0.0583        | 52.0  | 10192 | 0.9170   | 0.5335          |
| 0.0019        | 53.0  | 10388 | 0.9206   | 0.5843          |
| 0.0044        | 54.0  | 10584 | 0.9206   | 0.5895          |
| 0.0065        | 55.0  | 10780 | 0.9350   | 0.4487          |
| 0.0126        | 56.0  | 10976 | 0.9314   | 0.6221          |
| 0.0093        | 57.0  | 11172 | 0.9314   | 0.5138          |
| 0.0004        | 58.0  | 11368 | 0.9314   | 0.5162          |
| 0.0002        | 59.0  | 11564 | 0.9350   | 0.4514          |
| 0.1463        | 60.0  | 11760 | 0.9386   | 0.4744          |
| 0.0001        | 61.0  | 11956 | 0.9314   | 0.5338          |
| 0.0006        | 62.0  | 12152 | 0.9278   | 0.5788          |
| 0.0269        | 63.0  | 12348 | 0.9278   | 0.5500          |
| 0.1           | 64.0  | 12544 | 0.9206   | 0.6467          |
| 0.0004        | 65.0  | 12740 | 0.9242   | 0.5828          |
| 0.0001        | 66.0  | 12936 | 0.9314   | 0.5283          |
| 0.0001        | 67.0  | 13132 | 0.9206   | 0.6212          |
| 0.0002        | 68.0  | 13328 | 0.9242   | 0.4973          |
| 0.0058        | 69.0  | 13524 | 0.9278   | 0.5021          |
| 0.0605        | 70.0  | 13720 | 0.9170   | 0.6982          |
| 0.0006        | 71.0  | 13916 | 0.9350   | 0.4602          |
| 0.0021        | 72.0  | 14112 | 0.9314   | 0.5595          |
| 0.0004        | 73.0  | 14308 | 0.9386   | 0.4366          |
| 0.0124        | 74.0  | 14504 | 0.9134   | 0.7612          |
| 0.0284        | 75.0  | 14700 | 0.9206   | 0.6054          |
| 0.0001        | 76.0  | 14896 | 0.9242   | 0.5922          |
| 0.0119        | 77.0  | 15092 | 0.9242   | 0.5496          |
| 0.0006        | 78.0  | 15288 | 0.9206   | 0.6327          |
| 0.0711        | 79.0  | 15484 | 0.9386   | 0.5177          |
| 0.0001        | 80.0  | 15680 | 0.9134   | 0.7391          |
| 0.0985        | 81.0  | 15876 | 0.9242   | 0.5683          |
| 0.0001        | 82.0  | 16072 | 0.9206   | 0.6106          |
| 0.0           | 83.0  | 16268 | 0.9242   | 0.6235          |
| 0.0006        | 84.0  | 16464 | 0.9061   | 0.7914          |
| 0.0001        | 85.0  | 16660 | 0.9314   | 0.5649          |
| 0.0           | 86.0  | 16856 | 0.9350   | 0.5512          |
| 0.066         | 87.0  | 17052 | 0.9350   | 0.5473          |
| 0.0189        | 88.0  | 17248 | 0.9386   | 0.4866          |
| 0.0           | 89.0  | 17444 | 0.9386   | 0.5136          |
| 0.0001        | 90.0  | 17640 | 0.9350   | 0.5246          |
| 0.0001        | 91.0  | 17836 | 0.9314   | 0.5626          |
| 0.0037        | 92.0  | 18032 | 0.9350   | 0.5335          |
| 0.0999        | 93.0  | 18228 | 0.9242   | 0.6357          |
| 0.1124        | 94.0  | 18424 | 0.9278   | 0.5905          |
| 0.0175        | 95.0  | 18620 | 0.9206   | 0.6618          |
| 0.0001        | 96.0  | 18816 | 0.9386   | 0.5588          |
| 0.0259        | 97.0  | 19012 | 0.9350   | 0.5549          |
| 0.0001        | 98.0  | 19208 | 0.9350   | 0.5599          |
| 0.0285        | 99.0  | 19404 | 0.9350   | 0.5517          |
| 0.003         | 100.0 | 19600 | 0.9350   | 0.5570          |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0

fermentado hongo insecto insufi_fermen pizarroso violeta