metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_rms_001_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: 0.5777777777777777
hushem_40x_deit_base_rms_001_fold2
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 8.5594
- Accuracy: 0.5778
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: 0.001
- 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 |
|---|---|---|---|---|
| 1.1732 | 1.0 | 215 | 1.0108 | 0.4667 |
| 0.7763 | 2.0 | 430 | 1.2138 | 0.5333 |
| 0.7021 | 3.0 | 645 | 1.2446 | 0.4 |
| 0.6002 | 4.0 | 860 | 1.7707 | 0.4444 |
| 0.4988 | 5.0 | 1075 | 2.1116 | 0.4667 |
| 0.4269 | 6.0 | 1290 | 2.3849 | 0.5556 |
| 0.3366 | 7.0 | 1505 | 2.4322 | 0.5556 |
| 0.2961 | 8.0 | 1720 | 3.2646 | 0.5556 |
| 0.2377 | 9.0 | 1935 | 3.1438 | 0.5333 |
| 0.2435 | 10.0 | 2150 | 3.6031 | 0.5778 |
| 0.2593 | 11.0 | 2365 | 3.5951 | 0.4889 |
| 0.1482 | 12.0 | 2580 | 3.8372 | 0.5111 |
| 0.1871 | 13.0 | 2795 | 3.7490 | 0.6222 |
| 0.1246 | 14.0 | 3010 | 3.7977 | 0.5333 |
| 0.166 | 15.0 | 3225 | 3.7321 | 0.5778 |
| 0.1672 | 16.0 | 3440 | 4.6413 | 0.4889 |
| 0.1752 | 17.0 | 3655 | 4.9330 | 0.5556 |
| 0.1214 | 18.0 | 3870 | 4.3615 | 0.5556 |
| 0.0488 | 19.0 | 4085 | 4.4231 | 0.5111 |
| 0.1336 | 20.0 | 4300 | 4.4451 | 0.5778 |
| 0.1002 | 21.0 | 4515 | 3.7455 | 0.5778 |
| 0.0734 | 22.0 | 4730 | 4.4970 | 0.5556 |
| 0.0322 | 23.0 | 4945 | 4.8990 | 0.5333 |
| 0.214 | 24.0 | 5160 | 5.1865 | 0.5778 |
| 0.1242 | 25.0 | 5375 | 5.0088 | 0.5333 |
| 0.0033 | 26.0 | 5590 | 4.9606 | 0.5556 |
| 0.0333 | 27.0 | 5805 | 4.4063 | 0.5778 |
| 0.0592 | 28.0 | 6020 | 4.1719 | 0.5556 |
| 0.0444 | 29.0 | 6235 | 6.2342 | 0.5111 |
| 0.0039 | 30.0 | 6450 | 5.9834 | 0.5333 |
| 0.003 | 31.0 | 6665 | 6.2329 | 0.5333 |
| 0.0008 | 32.0 | 6880 | 6.2499 | 0.6 |
| 0.1078 | 33.0 | 7095 | 5.2542 | 0.6222 |
| 0.0258 | 34.0 | 7310 | 6.7980 | 0.4889 |
| 0.0052 | 35.0 | 7525 | 6.6849 | 0.5333 |
| 0.0003 | 36.0 | 7740 | 6.1342 | 0.5556 |
| 0.0005 | 37.0 | 7955 | 5.4920 | 0.5778 |
| 0.0004 | 38.0 | 8170 | 5.3684 | 0.5778 |
| 0.0148 | 39.0 | 8385 | 5.3551 | 0.5556 |
| 0.0054 | 40.0 | 8600 | 7.4300 | 0.5111 |
| 0.0 | 41.0 | 8815 | 6.8539 | 0.5556 |
| 0.0 | 42.0 | 9030 | 6.8688 | 0.5556 |
| 0.0 | 43.0 | 9245 | 7.1702 | 0.5778 |
| 0.0 | 44.0 | 9460 | 7.4631 | 0.5778 |
| 0.0 | 45.0 | 9675 | 7.7338 | 0.5778 |
| 0.0 | 46.0 | 9890 | 7.9825 | 0.5778 |
| 0.0 | 47.0 | 10105 | 8.2172 | 0.5778 |
| 0.0 | 48.0 | 10320 | 8.4047 | 0.5778 |
| 0.0 | 49.0 | 10535 | 8.5267 | 0.5778 |
| 0.0 | 50.0 | 10750 | 8.5594 | 0.5778 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2