metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_rms_0001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5555555555555556
hushem_1x_deit_tiny_rms_0001_fold2
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 3.1133
- Accuracy: 0.5556
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.9323 | 0.2444 |
| 2.0865 | 2.0 | 12 | 1.4427 | 0.2444 |
| 2.0865 | 3.0 | 18 | 1.4293 | 0.2444 |
| 1.4431 | 4.0 | 24 | 1.3952 | 0.4667 |
| 1.4003 | 5.0 | 30 | 1.2967 | 0.4 |
| 1.4003 | 6.0 | 36 | 1.4719 | 0.2444 |
| 1.3496 | 7.0 | 42 | 1.3224 | 0.3556 |
| 1.3496 | 8.0 | 48 | 1.4673 | 0.3778 |
| 1.2064 | 9.0 | 54 | 1.4551 | 0.2667 |
| 1.1859 | 10.0 | 60 | 1.3687 | 0.3111 |
| 1.1859 | 11.0 | 66 | 1.2313 | 0.4444 |
| 1.0817 | 12.0 | 72 | 1.1514 | 0.4444 |
| 1.0817 | 13.0 | 78 | 1.1701 | 0.4444 |
| 1.0144 | 14.0 | 84 | 1.2204 | 0.4222 |
| 0.8578 | 15.0 | 90 | 1.1603 | 0.4889 |
| 0.8578 | 16.0 | 96 | 1.0987 | 0.5111 |
| 0.8063 | 17.0 | 102 | 0.9277 | 0.5111 |
| 0.8063 | 18.0 | 108 | 1.2038 | 0.5333 |
| 0.601 | 19.0 | 114 | 0.9886 | 0.6 |
| 0.465 | 20.0 | 120 | 1.5667 | 0.5111 |
| 0.465 | 21.0 | 126 | 1.8238 | 0.4889 |
| 0.2956 | 22.0 | 132 | 1.6043 | 0.4222 |
| 0.2956 | 23.0 | 138 | 1.2746 | 0.4889 |
| 0.3513 | 24.0 | 144 | 1.6389 | 0.5556 |
| 0.2137 | 25.0 | 150 | 1.6350 | 0.4889 |
| 0.2137 | 26.0 | 156 | 1.5926 | 0.4667 |
| 0.191 | 27.0 | 162 | 1.8516 | 0.4889 |
| 0.191 | 28.0 | 168 | 2.3628 | 0.4889 |
| 0.0581 | 29.0 | 174 | 2.3998 | 0.4889 |
| 0.0517 | 30.0 | 180 | 2.3913 | 0.5333 |
| 0.0517 | 31.0 | 186 | 2.7108 | 0.5556 |
| 0.005 | 32.0 | 192 | 2.8104 | 0.5556 |
| 0.005 | 33.0 | 198 | 2.8829 | 0.5556 |
| 0.0008 | 34.0 | 204 | 2.9326 | 0.5333 |
| 0.0006 | 35.0 | 210 | 2.9793 | 0.5556 |
| 0.0006 | 36.0 | 216 | 3.0150 | 0.5556 |
| 0.0005 | 37.0 | 222 | 3.0520 | 0.5556 |
| 0.0005 | 38.0 | 228 | 3.0772 | 0.5556 |
| 0.0004 | 39.0 | 234 | 3.0948 | 0.5556 |
| 0.0004 | 40.0 | 240 | 3.1038 | 0.5556 |
| 0.0004 | 41.0 | 246 | 3.1116 | 0.5556 |
| 0.0004 | 42.0 | 252 | 3.1133 | 0.5556 |
| 0.0004 | 43.0 | 258 | 3.1133 | 0.5556 |
| 0.0004 | 44.0 | 264 | 3.1133 | 0.5556 |
| 0.0004 | 45.0 | 270 | 3.1133 | 0.5556 |
| 0.0004 | 46.0 | 276 | 3.1133 | 0.5556 |
| 0.0004 | 47.0 | 282 | 3.1133 | 0.5556 |
| 0.0004 | 48.0 | 288 | 3.1133 | 0.5556 |
| 0.0004 | 49.0 | 294 | 3.1133 | 0.5556 |
| 0.0004 | 50.0 | 300 | 3.1133 | 0.5556 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1