|
---
|
|
base_model: MBZUAI/swiftformer-xs
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagefolder
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: swiftformer-xs-ve-U13-b-80e
|
|
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: 0.8478260869565217
|
|
---
|
|
|
|
<!-- 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. -->
|
|
|
|
# swiftformer-xs-ve-U13-b-80e
|
|
|
|
This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co./MBZUAI/swiftformer-xs) on the imagefolder dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.6618
|
|
- Accuracy: 0.8478
|
|
|
|
## 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: 0.0003
|
|
- 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: 0.15
|
|
- num_epochs: 80
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| No log | 0.92 | 6 | 1.3859 | 0.2391 |
|
|
| 1.3857 | 2.0 | 13 | 1.3834 | 0.3261 |
|
|
| 1.3857 | 2.92 | 19 | 1.3789 | 0.1957 |
|
|
| 1.3767 | 4.0 | 26 | 1.3666 | 0.1739 |
|
|
| 1.3227 | 4.92 | 32 | 1.3565 | 0.1522 |
|
|
| 1.3227 | 6.0 | 39 | 1.3887 | 0.1087 |
|
|
| 1.1987 | 6.92 | 45 | 1.3719 | 0.2174 |
|
|
| 1.1071 | 8.0 | 52 | 1.3271 | 0.3043 |
|
|
| 1.1071 | 8.92 | 58 | 1.3562 | 0.2609 |
|
|
| 0.9926 | 10.0 | 65 | 1.2306 | 0.4130 |
|
|
| 0.8721 | 10.92 | 71 | 1.1953 | 0.4565 |
|
|
| 0.8721 | 12.0 | 78 | 1.0754 | 0.5652 |
|
|
| 0.7746 | 12.92 | 84 | 0.9931 | 0.6739 |
|
|
| 0.6859 | 14.0 | 91 | 0.9979 | 0.6739 |
|
|
| 0.6859 | 14.92 | 97 | 0.8964 | 0.6957 |
|
|
| 0.5777 | 16.0 | 104 | 0.9186 | 0.6522 |
|
|
| 0.5136 | 16.92 | 110 | 0.7950 | 0.7609 |
|
|
| 0.5136 | 18.0 | 117 | 0.7794 | 0.7391 |
|
|
| 0.5019 | 18.92 | 123 | 0.8645 | 0.7174 |
|
|
| 0.3879 | 20.0 | 130 | 0.8773 | 0.6957 |
|
|
| 0.3879 | 20.92 | 136 | 0.7304 | 0.7609 |
|
|
| 0.3532 | 22.0 | 143 | 0.6918 | 0.7609 |
|
|
| 0.3532 | 22.92 | 149 | 0.7882 | 0.7609 |
|
|
| 0.3288 | 24.0 | 156 | 0.7132 | 0.7609 |
|
|
| 0.2573 | 24.92 | 162 | 0.6645 | 0.8043 |
|
|
| 0.2573 | 26.0 | 169 | 0.6618 | 0.8478 |
|
|
| 0.239 | 26.92 | 175 | 0.6780 | 0.8043 |
|
|
| 0.2018 | 28.0 | 182 | 0.8138 | 0.6957 |
|
|
| 0.2018 | 28.92 | 188 | 0.8797 | 0.6957 |
|
|
| 0.1961 | 30.0 | 195 | 0.8602 | 0.7174 |
|
|
| 0.214 | 30.92 | 201 | 0.8188 | 0.7391 |
|
|
| 0.214 | 32.0 | 208 | 0.6956 | 0.7609 |
|
|
| 0.1596 | 32.92 | 214 | 0.7981 | 0.7391 |
|
|
| 0.172 | 34.0 | 221 | 0.6845 | 0.7609 |
|
|
| 0.172 | 34.92 | 227 | 0.9340 | 0.7174 |
|
|
| 0.1852 | 36.0 | 234 | 0.9548 | 0.6522 |
|
|
| 0.1492 | 36.92 | 240 | 0.7747 | 0.7609 |
|
|
| 0.1492 | 38.0 | 247 | 0.9907 | 0.6304 |
|
|
| 0.1735 | 38.92 | 253 | 0.8040 | 0.7174 |
|
|
| 0.1405 | 40.0 | 260 | 0.6946 | 0.7609 |
|
|
| 0.1405 | 40.92 | 266 | 0.7019 | 0.7609 |
|
|
| 0.1269 | 42.0 | 273 | 0.8246 | 0.7174 |
|
|
| 0.1269 | 42.92 | 279 | 0.9238 | 0.6739 |
|
|
| 0.1237 | 44.0 | 286 | 0.9354 | 0.6957 |
|
|
| 0.1201 | 44.92 | 292 | 0.7543 | 0.7391 |
|
|
| 0.1201 | 46.0 | 299 | 0.7151 | 0.7174 |
|
|
| 0.1134 | 46.92 | 305 | 0.7284 | 0.7174 |
|
|
| 0.1141 | 48.0 | 312 | 0.7791 | 0.7609 |
|
|
| 0.1141 | 48.92 | 318 | 0.7824 | 0.7391 |
|
|
| 0.1253 | 50.0 | 325 | 0.7319 | 0.7609 |
|
|
| 0.0968 | 50.92 | 331 | 0.7151 | 0.7609 |
|
|
| 0.0968 | 52.0 | 338 | 0.7662 | 0.7609 |
|
|
| 0.0996 | 52.92 | 344 | 0.8086 | 0.7826 |
|
|
| 0.0844 | 54.0 | 351 | 0.8921 | 0.7609 |
|
|
| 0.0844 | 54.92 | 357 | 0.8782 | 0.7609 |
|
|
| 0.1141 | 56.0 | 364 | 0.7864 | 0.7391 |
|
|
| 0.1263 | 56.92 | 370 | 0.7125 | 0.7609 |
|
|
| 0.1263 | 58.0 | 377 | 0.6758 | 0.7609 |
|
|
| 0.0966 | 58.92 | 383 | 0.7243 | 0.7609 |
|
|
| 0.0771 | 60.0 | 390 | 0.7090 | 0.7609 |
|
|
| 0.0771 | 60.92 | 396 | 0.7157 | 0.7609 |
|
|
| 0.0497 | 62.0 | 403 | 0.7549 | 0.7609 |
|
|
| 0.0497 | 62.92 | 409 | 0.7806 | 0.7609 |
|
|
| 0.0848 | 64.0 | 416 | 0.7902 | 0.7391 |
|
|
| 0.0477 | 64.92 | 422 | 0.7684 | 0.7391 |
|
|
| 0.0477 | 66.0 | 429 | 0.8038 | 0.6957 |
|
|
| 0.0823 | 66.92 | 435 | 0.7503 | 0.6957 |
|
|
| 0.0726 | 68.0 | 442 | 0.7634 | 0.7609 |
|
|
| 0.0726 | 68.92 | 448 | 0.7860 | 0.7826 |
|
|
| 0.0799 | 70.0 | 455 | 0.7630 | 0.7609 |
|
|
| 0.067 | 70.92 | 461 | 0.8094 | 0.7391 |
|
|
| 0.067 | 72.0 | 468 | 0.7511 | 0.7391 |
|
|
| 0.0893 | 72.92 | 474 | 0.7738 | 0.7391 |
|
|
| 0.0738 | 73.85 | 480 | 0.7971 | 0.7391 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.36.2
|
|
- Pytorch 2.1.2+cu118
|
|
- Datasets 2.16.1
|
|
- Tokenizers 0.15.0
|
|
|
