|
|
---
|
|
|
license: apache-2.0
|
|
|
base_model: microsoft/swinv2-tiny-patch4-window8-256
|
|
|
tags:
|
|
|
- generated_from_trainer
|
|
|
datasets:
|
|
|
- imagefolder
|
|
|
metrics:
|
|
|
- accuracy
|
|
|
model-index:
|
|
|
- name: SW2-DMAE-DA
|
|
|
results:
|
|
|
- task:
|
|
|
name: Image Classification
|
|
|
type: image-classification
|
|
|
dataset:
|
|
|
name: imagefolder
|
|
|
type: imagefolder
|
|
|
config: default
|
|
|
split: validation
|
|
|
args: default
|
|
|
metrics:
|
|
|
- name: Accuracy
|
|
|
type: accuracy
|
|
|
value: 0.6304347826086957
|
|
|
---
|
|
|
|
|
|
<!-- 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. -->
|
|
|
|
|
|
# SW2-DMAE-DA
|
|
|
|
|
|
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
|
|
|
It achieves the following results on the evaluation set:
|
|
|
- Loss: 0.8856
|
|
|
- Accuracy: 0.6304
|
|
|
|
|
|
## 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: 4e-05
|
|
|
- train_batch_size: 16
|
|
|
- eval_batch_size: 16
|
|
|
- seed: 42
|
|
|
- gradient_accumulation_steps: 4
|
|
|
- total_train_batch_size: 64
|
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
|
- lr_scheduler_type: linear
|
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
|
- num_epochs: 40
|
|
|
|
|
|
### Training results
|
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
|
| 6.464 | 0.96 | 11 | 7.9190 | 0.1087 |
|
|
|
| 6.5496 | 2.0 | 23 | 7.5824 | 0.1087 |
|
|
|
| 6.1541 | 2.96 | 34 | 6.4156 | 0.1087 |
|
|
|
| 5.2649 | 4.0 | 46 | 4.5067 | 0.1087 |
|
|
|
| 4.1175 | 4.96 | 57 | 2.7241 | 0.1087 |
|
|
|
| 2.8424 | 6.0 | 69 | 1.5623 | 0.1087 |
|
|
|
| 1.4376 | 6.96 | 80 | 1.4003 | 0.1087 |
|
|
|
| 1.4054 | 8.0 | 92 | 1.4055 | 0.1087 |
|
|
|
| 1.3798 | 8.96 | 103 | 1.3466 | 0.4565 |
|
|
|
| 1.3331 | 10.0 | 115 | 1.4385 | 0.1522 |
|
|
|
| 1.2736 | 10.96 | 126 | 1.3106 | 0.2391 |
|
|
|
| 1.2127 | 12.0 | 138 | 1.2908 | 0.1957 |
|
|
|
| 1.2531 | 12.96 | 149 | 1.2545 | 0.5 |
|
|
|
| 1.0972 | 14.0 | 161 | 1.2515 | 0.3478 |
|
|
|
| 1.0029 | 14.96 | 172 | 1.2238 | 0.2609 |
|
|
|
| 1.0141 | 16.0 | 184 | 1.2067 | 0.3696 |
|
|
|
| 0.9129 | 16.96 | 195 | 1.1149 | 0.5652 |
|
|
|
| 0.9157 | 18.0 | 207 | 1.1957 | 0.3913 |
|
|
|
| 0.8516 | 18.96 | 218 | 1.0034 | 0.5435 |
|
|
|
| 0.7804 | 20.0 | 230 | 0.9991 | 0.4783 |
|
|
|
| 0.7328 | 20.96 | 241 | 0.9840 | 0.5870 |
|
|
|
| 0.7101 | 22.0 | 253 | 0.9661 | 0.5435 |
|
|
|
| 0.7099 | 22.96 | 264 | 0.9392 | 0.5435 |
|
|
|
| 0.7238 | 24.0 | 276 | 0.9553 | 0.5 |
|
|
|
| 0.6605 | 24.96 | 287 | 0.9571 | 0.5435 |
|
|
|
| 0.639 | 26.0 | 299 | 1.0534 | 0.5652 |
|
|
|
| 0.6123 | 26.96 | 310 | 0.9152 | 0.6087 |
|
|
|
| 0.6021 | 28.0 | 322 | 0.8704 | 0.5870 |
|
|
|
| 0.5971 | 28.96 | 333 | 0.8726 | 0.5652 |
|
|
|
| 0.5413 | 30.0 | 345 | 0.8287 | 0.5870 |
|
|
|
| 0.5663 | 30.96 | 356 | 0.9271 | 0.5435 |
|
|
|
| 0.5343 | 32.0 | 368 | 0.8856 | 0.6304 |
|
|
|
| 0.525 | 32.96 | 379 | 0.8579 | 0.6087 |
|
|
|
| 0.5447 | 34.0 | 391 | 0.8746 | 0.5870 |
|
|
|
| 0.5036 | 34.96 | 402 | 0.8684 | 0.5652 |
|
|
|
| 0.4918 | 36.0 | 414 | 0.8268 | 0.5870 |
|
|
|
| 0.503 | 36.96 | 425 | 0.8374 | 0.5870 |
|
|
|
| 0.5114 | 38.0 | 437 | 0.8380 | 0.6087 |
|
|
|
| 0.5272 | 38.26 | 440 | 0.8387 | 0.6087 |
|
|
|
|
|
|
|
|
|
### Framework versions
|
|
|
|
|
|
- Transformers 4.36.2
|
|
|
- Pytorch 2.1.2+cu118
|
|
|
- Datasets 2.16.1
|
|
|
- Tokenizers 0.15.0
|
|
|
|
