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# deit-base-distilled-patch16-224-65-fold4

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5367
- Accuracy: 0.8451

## 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: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9231  | 3    | 0.7145          | 0.5211   |
| No log        | 1.8462  | 6    | 0.7082          | 0.5070   |
| No log        | 2.7692  | 9    | 0.6889          | 0.6056   |
| 0.6878        | 4.0     | 13   | 0.6703          | 0.6620   |
| 0.6878        | 4.9231  | 16   | 0.6556          | 0.6761   |
| 0.6878        | 5.8462  | 19   | 0.6430          | 0.6620   |
| 0.6203        | 6.7692  | 22   | 0.6250          | 0.6761   |
| 0.6203        | 8.0     | 26   | 0.7464          | 0.6197   |
| 0.6203        | 8.9231  | 29   | 0.6647          | 0.6056   |
| 0.5703        | 9.8462  | 32   | 0.6097          | 0.7042   |
| 0.5703        | 10.7692 | 35   | 0.6261          | 0.6620   |
| 0.5703        | 12.0    | 39   | 0.5926          | 0.7042   |
| 0.5281        | 12.9231 | 42   | 0.5370          | 0.7465   |
| 0.5281        | 13.8462 | 45   | 0.5638          | 0.7465   |
| 0.5281        | 14.7692 | 48   | 0.7175          | 0.6056   |
| 0.4616        | 16.0    | 52   | 0.8917          | 0.5775   |
| 0.4616        | 16.9231 | 55   | 0.6761          | 0.6761   |
| 0.4616        | 17.8462 | 58   | 0.5606          | 0.7324   |
| 0.4943        | 18.7692 | 61   | 0.6963          | 0.6338   |
| 0.4943        | 20.0    | 65   | 0.6462          | 0.6620   |
| 0.4943        | 20.9231 | 68   | 0.6246          | 0.7183   |
| 0.4058        | 21.8462 | 71   | 0.7336          | 0.6620   |
| 0.4058        | 22.7692 | 74   | 0.6270          | 0.7324   |
| 0.4058        | 24.0    | 78   | 0.6097          | 0.7183   |
| 0.3577        | 24.9231 | 81   | 0.6700          | 0.7606   |
| 0.3577        | 25.8462 | 84   | 0.6676          | 0.7183   |
| 0.3577        | 26.7692 | 87   | 0.5475          | 0.7887   |
| 0.2988        | 28.0    | 91   | 0.5383          | 0.8028   |
| 0.2988        | 28.9231 | 94   | 0.5534          | 0.7183   |
| 0.2988        | 29.8462 | 97   | 0.5842          | 0.8028   |
| 0.2595        | 30.7692 | 100  | 0.5965          | 0.7887   |
| 0.2595        | 32.0    | 104  | 0.6220          | 0.7606   |
| 0.2595        | 32.9231 | 107  | 0.6027          | 0.7606   |
| 0.2422        | 33.8462 | 110  | 0.6369          | 0.7183   |
| 0.2422        | 34.7692 | 113  | 0.6033          | 0.7746   |
| 0.2422        | 36.0    | 117  | 0.6912          | 0.7324   |
| 0.1927        | 36.9231 | 120  | 0.6582          | 0.7887   |
| 0.1927        | 37.8462 | 123  | 0.6320          | 0.7746   |
| 0.1927        | 38.7692 | 126  | 0.7532          | 0.7606   |
| 0.2399        | 40.0    | 130  | 0.7909          | 0.7606   |
| 0.2399        | 40.9231 | 133  | 0.6808          | 0.7465   |
| 0.2399        | 41.8462 | 136  | 0.5816          | 0.7887   |
| 0.2399        | 42.7692 | 139  | 0.5474          | 0.7887   |
| 0.2218        | 44.0    | 143  | 0.6310          | 0.7042   |
| 0.2218        | 44.9231 | 146  | 0.6453          | 0.8028   |
| 0.2218        | 45.8462 | 149  | 0.6170          | 0.7887   |
| 0.1817        | 46.7692 | 152  | 0.6034          | 0.7887   |
| 0.1817        | 48.0    | 156  | 0.6350          | 0.8310   |
| 0.1817        | 48.9231 | 159  | 0.6027          | 0.7887   |
| 0.1483        | 49.8462 | 162  | 0.5599          | 0.8028   |
| 0.1483        | 50.7692 | 165  | 0.5817          | 0.8310   |
| 0.1483        | 52.0    | 169  | 0.6086          | 0.7746   |
| 0.1668        | 52.9231 | 172  | 0.5744          | 0.8169   |
| 0.1668        | 53.8462 | 175  | 0.6059          | 0.7887   |
| 0.1668        | 54.7692 | 178  | 0.6455          | 0.7887   |
| 0.1372        | 56.0    | 182  | 0.5367          | 0.8451   |
| 0.1372        | 56.9231 | 185  | 0.5615          | 0.8169   |
| 0.1372        | 57.8462 | 188  | 0.6378          | 0.8028   |
| 0.1485        | 58.7692 | 191  | 0.5687          | 0.8169   |
| 0.1485        | 60.0    | 195  | 0.4897          | 0.8169   |
| 0.1485        | 60.9231 | 198  | 0.4384          | 0.8451   |
| 0.1426        | 61.8462 | 201  | 0.5087          | 0.7887   |
| 0.1426        | 62.7692 | 204  | 0.4757          | 0.8169   |
| 0.1426        | 64.0    | 208  | 0.4373          | 0.8169   |
| 0.1333        | 64.9231 | 211  | 0.4512          | 0.8169   |
| 0.1333        | 65.8462 | 214  | 0.4619          | 0.7887   |
| 0.1333        | 66.7692 | 217  | 0.5520          | 0.8028   |
| 0.1306        | 68.0    | 221  | 0.5161          | 0.7887   |
| 0.1306        | 68.9231 | 224  | 0.5180          | 0.7606   |
| 0.1306        | 69.8462 | 227  | 0.5778          | 0.8028   |
| 0.1327        | 70.7692 | 230  | 0.5933          | 0.8028   |
| 0.1327        | 72.0    | 234  | 0.5222          | 0.7887   |
| 0.1327        | 72.9231 | 237  | 0.5104          | 0.8169   |
| 0.1171        | 73.8462 | 240  | 0.5024          | 0.8169   |
| 0.1171        | 74.7692 | 243  | 0.5060          | 0.8028   |
| 0.1171        | 76.0    | 247  | 0.5267          | 0.7746   |
| 0.1227        | 76.9231 | 250  | 0.4775          | 0.8169   |
| 0.1227        | 77.8462 | 253  | 0.5020          | 0.8169   |
| 0.1227        | 78.7692 | 256  | 0.5243          | 0.7606   |
| 0.1304        | 80.0    | 260  | 0.6195          | 0.7887   |
| 0.1304        | 80.9231 | 263  | 0.5740          | 0.7606   |
| 0.1304        | 81.8462 | 266  | 0.5652          | 0.8169   |
| 0.1304        | 82.7692 | 269  | 0.5750          | 0.8169   |
| 0.1152        | 84.0    | 273  | 0.5829          | 0.7887   |
| 0.1152        | 84.9231 | 276  | 0.5854          | 0.7887   |
| 0.1152        | 85.8462 | 279  | 0.5854          | 0.7887   |
| 0.1069        | 86.7692 | 282  | 0.5826          | 0.8028   |
| 0.1069        | 88.0    | 286  | 0.5839          | 0.7887   |
| 0.1069        | 88.9231 | 289  | 0.5792          | 0.8169   |
| 0.122         | 89.8462 | 292  | 0.5755          | 0.8169   |
| 0.122         | 90.7692 | 295  | 0.5751          | 0.8169   |
| 0.122         | 92.0    | 299  | 0.5748          | 0.8169   |
| 0.1268        | 92.3077 | 300  | 0.5748          | 0.8169   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hasta normal