|
--- |
|
license: apache-2.0 |
|
base_model: facebook/deit-base-distilled-patch16-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: deit-base-distilled-patch16-224-55-fold5 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8227848101265823 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# deit-base-distilled-patch16-224-55-fold5 |
|
|
|
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: 0.6452 |
|
- Accuracy: 0.8228 |
|
|
|
## 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 | 0.8571 | 3 | 0.7319 | 0.5190 | |
|
| No log | 2.0 | 7 | 0.6756 | 0.5696 | |
|
| 0.6544 | 2.8571 | 10 | 0.6199 | 0.6456 | |
|
| 0.6544 | 4.0 | 14 | 0.5987 | 0.6203 | |
|
| 0.6544 | 4.8571 | 17 | 0.5676 | 0.6709 | |
|
| 0.6173 | 6.0 | 21 | 0.6543 | 0.5823 | |
|
| 0.6173 | 6.8571 | 24 | 0.5310 | 0.7342 | |
|
| 0.6173 | 8.0 | 28 | 0.6724 | 0.6076 | |
|
| 0.5245 | 8.8571 | 31 | 0.6444 | 0.6582 | |
|
| 0.5245 | 10.0 | 35 | 0.5027 | 0.7342 | |
|
| 0.5245 | 10.8571 | 38 | 0.6328 | 0.6582 | |
|
| 0.4554 | 12.0 | 42 | 0.4883 | 0.7595 | |
|
| 0.4554 | 12.8571 | 45 | 0.6736 | 0.6582 | |
|
| 0.4554 | 14.0 | 49 | 0.4584 | 0.7342 | |
|
| 0.4575 | 14.8571 | 52 | 0.8099 | 0.6456 | |
|
| 0.4575 | 16.0 | 56 | 0.4767 | 0.7468 | |
|
| 0.4575 | 16.8571 | 59 | 0.6059 | 0.6835 | |
|
| 0.3798 | 18.0 | 63 | 0.4863 | 0.7595 | |
|
| 0.3798 | 18.8571 | 66 | 0.5636 | 0.7468 | |
|
| 0.3419 | 20.0 | 70 | 0.4677 | 0.7342 | |
|
| 0.3419 | 20.8571 | 73 | 0.4883 | 0.7089 | |
|
| 0.3419 | 22.0 | 77 | 0.5549 | 0.7215 | |
|
| 0.3079 | 22.8571 | 80 | 0.4324 | 0.7848 | |
|
| 0.3079 | 24.0 | 84 | 0.6184 | 0.6709 | |
|
| 0.3079 | 24.8571 | 87 | 0.6149 | 0.7089 | |
|
| 0.2616 | 26.0 | 91 | 0.4488 | 0.7848 | |
|
| 0.2616 | 26.8571 | 94 | 0.4368 | 0.7722 | |
|
| 0.2616 | 28.0 | 98 | 0.4566 | 0.7722 | |
|
| 0.2157 | 28.8571 | 101 | 0.4657 | 0.7848 | |
|
| 0.2157 | 30.0 | 105 | 0.4514 | 0.7722 | |
|
| 0.2157 | 30.8571 | 108 | 0.5083 | 0.7848 | |
|
| 0.2258 | 32.0 | 112 | 0.5261 | 0.7848 | |
|
| 0.2258 | 32.8571 | 115 | 0.5567 | 0.7595 | |
|
| 0.2258 | 34.0 | 119 | 0.5566 | 0.8101 | |
|
| 0.1972 | 34.8571 | 122 | 0.5495 | 0.8101 | |
|
| 0.1972 | 36.0 | 126 | 0.4992 | 0.7975 | |
|
| 0.1972 | 36.8571 | 129 | 0.5661 | 0.7595 | |
|
| 0.1709 | 38.0 | 133 | 0.7326 | 0.7342 | |
|
| 0.1709 | 38.8571 | 136 | 0.5635 | 0.8101 | |
|
| 0.1537 | 40.0 | 140 | 0.8130 | 0.7468 | |
|
| 0.1537 | 40.8571 | 143 | 0.6984 | 0.7848 | |
|
| 0.1537 | 42.0 | 147 | 0.7777 | 0.7595 | |
|
| 0.1687 | 42.8571 | 150 | 0.6452 | 0.8228 | |
|
| 0.1687 | 44.0 | 154 | 0.8527 | 0.7215 | |
|
| 0.1687 | 44.8571 | 157 | 0.6483 | 0.7975 | |
|
| 0.1588 | 46.0 | 161 | 0.8185 | 0.7342 | |
|
| 0.1588 | 46.8571 | 164 | 0.6821 | 0.7722 | |
|
| 0.1588 | 48.0 | 168 | 0.7594 | 0.7342 | |
|
| 0.144 | 48.8571 | 171 | 1.0232 | 0.7595 | |
|
| 0.144 | 50.0 | 175 | 0.6178 | 0.7848 | |
|
| 0.144 | 50.8571 | 178 | 0.6243 | 0.7595 | |
|
| 0.1449 | 52.0 | 182 | 0.8159 | 0.7342 | |
|
| 0.1449 | 52.8571 | 185 | 0.6664 | 0.7722 | |
|
| 0.1449 | 54.0 | 189 | 0.7070 | 0.7342 | |
|
| 0.144 | 54.8571 | 192 | 0.7361 | 0.7468 | |
|
| 0.144 | 56.0 | 196 | 0.6656 | 0.7595 | |
|
| 0.144 | 56.8571 | 199 | 0.7487 | 0.7468 | |
|
| 0.1199 | 58.0 | 203 | 0.7993 | 0.7342 | |
|
| 0.1199 | 58.8571 | 206 | 0.7426 | 0.7722 | |
|
| 0.1258 | 60.0 | 210 | 0.7531 | 0.7975 | |
|
| 0.1258 | 60.8571 | 213 | 0.7388 | 0.7848 | |
|
| 0.1258 | 62.0 | 217 | 0.7395 | 0.7975 | |
|
| 0.1392 | 62.8571 | 220 | 0.8238 | 0.7468 | |
|
| 0.1392 | 64.0 | 224 | 0.9302 | 0.7215 | |
|
| 0.1392 | 64.8571 | 227 | 0.7539 | 0.7722 | |
|
| 0.1303 | 66.0 | 231 | 0.6739 | 0.8101 | |
|
| 0.1303 | 66.8571 | 234 | 0.6627 | 0.7848 | |
|
| 0.1303 | 68.0 | 238 | 0.6403 | 0.7848 | |
|
| 0.1423 | 68.8571 | 241 | 0.6379 | 0.7975 | |
|
| 0.1423 | 70.0 | 245 | 0.7658 | 0.7595 | |
|
| 0.1423 | 70.8571 | 248 | 0.9195 | 0.7342 | |
|
| 0.1019 | 72.0 | 252 | 0.7287 | 0.7722 | |
|
| 0.1019 | 72.8571 | 255 | 0.6548 | 0.7975 | |
|
| 0.1019 | 74.0 | 259 | 0.6534 | 0.7848 | |
|
| 0.1286 | 74.8571 | 262 | 0.7331 | 0.7848 | |
|
| 0.1286 | 76.0 | 266 | 0.7845 | 0.7595 | |
|
| 0.1286 | 76.8571 | 269 | 0.7188 | 0.7975 | |
|
| 0.1054 | 78.0 | 273 | 0.6595 | 0.7722 | |
|
| 0.1054 | 78.8571 | 276 | 0.6623 | 0.7722 | |
|
| 0.1053 | 80.0 | 280 | 0.7337 | 0.7722 | |
|
| 0.1053 | 80.8571 | 283 | 0.8085 | 0.7468 | |
|
| 0.1053 | 82.0 | 287 | 0.8201 | 0.7468 | |
|
| 0.1086 | 82.8571 | 290 | 0.7947 | 0.7468 | |
|
| 0.1086 | 84.0 | 294 | 0.7669 | 0.7722 | |
|
| 0.1086 | 84.8571 | 297 | 0.7582 | 0.7595 | |
|
| 0.1186 | 85.7143 | 300 | 0.7541 | 0.7595 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
