metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_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: 0.6888888888888889
hushem_40x_beit_large_adamax_001_fold2
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 4.4537
- Accuracy: 0.6889
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 |
|---|---|---|---|---|
| 0.3184 | 1.0 | 215 | 1.1233 | 0.7333 |
| 0.1436 | 2.0 | 430 | 1.6198 | 0.6889 |
| 0.047 | 3.0 | 645 | 1.8592 | 0.6667 |
| 0.0527 | 4.0 | 860 | 1.5842 | 0.7111 |
| 0.0463 | 5.0 | 1075 | 2.7619 | 0.6889 |
| 0.0137 | 6.0 | 1290 | 1.4680 | 0.7556 |
| 0.0665 | 7.0 | 1505 | 2.2491 | 0.6889 |
| 0.0121 | 8.0 | 1720 | 1.7706 | 0.7556 |
| 0.0005 | 9.0 | 1935 | 2.1035 | 0.7556 |
| 0.0192 | 10.0 | 2150 | 3.0002 | 0.6889 |
| 0.02 | 11.0 | 2365 | 2.1406 | 0.6667 |
| 0.011 | 12.0 | 2580 | 2.2828 | 0.6667 |
| 0.0346 | 13.0 | 2795 | 2.5178 | 0.6667 |
| 0.0045 | 14.0 | 3010 | 2.0578 | 0.7333 |
| 0.0021 | 15.0 | 3225 | 1.4918 | 0.7556 |
| 0.0002 | 16.0 | 3440 | 2.6023 | 0.7111 |
| 0.0007 | 17.0 | 3655 | 2.4242 | 0.7111 |
| 0.0019 | 18.0 | 3870 | 2.8391 | 0.6667 |
| 0.0005 | 19.0 | 4085 | 2.9921 | 0.7556 |
| 0.0 | 20.0 | 4300 | 3.1529 | 0.6667 |
| 0.0 | 21.0 | 4515 | 2.7412 | 0.7556 |
| 0.0 | 22.0 | 4730 | 2.8583 | 0.7333 |
| 0.0 | 23.0 | 4945 | 2.9971 | 0.7333 |
| 0.0 | 24.0 | 5160 | 3.0142 | 0.7556 |
| 0.0 | 25.0 | 5375 | 3.0328 | 0.7556 |
| 0.0 | 26.0 | 5590 | 3.0307 | 0.7778 |
| 0.0 | 27.0 | 5805 | 3.2285 | 0.7556 |
| 0.0 | 28.0 | 6020 | 3.2719 | 0.7111 |
| 0.0 | 29.0 | 6235 | 2.7270 | 0.7778 |
| 0.0 | 30.0 | 6450 | 3.4979 | 0.7111 |
| 0.0 | 31.0 | 6665 | 3.4752 | 0.7333 |
| 0.0 | 32.0 | 6880 | 3.4952 | 0.7333 |
| 0.0 | 33.0 | 7095 | 3.5111 | 0.7333 |
| 0.0 | 34.0 | 7310 | 3.5230 | 0.7333 |
| 0.0 | 35.0 | 7525 | 3.5422 | 0.7333 |
| 0.0 | 36.0 | 7740 | 3.5606 | 0.7333 |
| 0.0 | 37.0 | 7955 | 3.5754 | 0.7333 |
| 0.0 | 38.0 | 8170 | 3.5859 | 0.7333 |
| 0.0 | 39.0 | 8385 | 3.5773 | 0.7333 |
| 0.0 | 40.0 | 8600 | 4.7039 | 0.6 |
| 0.0 | 41.0 | 8815 | 4.7831 | 0.6 |
| 0.0 | 42.0 | 9030 | 4.4812 | 0.6667 |
| 0.0 | 43.0 | 9245 | 4.4224 | 0.6889 |
| 0.0 | 44.0 | 9460 | 4.4294 | 0.6889 |
| 0.0 | 45.0 | 9675 | 4.4285 | 0.6889 |
| 0.0 | 46.0 | 9890 | 4.4304 | 0.6889 |
| 0.0 | 47.0 | 10105 | 4.4476 | 0.6889 |
| 0.0 | 48.0 | 10320 | 4.4513 | 0.6889 |
| 0.0 | 49.0 | 10535 | 4.4531 | 0.6889 |
| 0.0 | 50.0 | 10750 | 4.4537 | 0.6889 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2