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---
license: other
base_model: apple/mobilevitv2-1.0-imagenet1k-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-trained-task3
results: []
---
<!-- 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. -->
# mobilevit-trained-task3
This model is a fine-tuned version of [apple/mobilevitv2-1.0-imagenet1k-256](https://huggingface.co/apple/mobilevitv2-1.0-imagenet1k-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1371
- Accuracy: 0.9670
## 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
- 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: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6753 | 0.99 | 126 | 0.8382 | 0.7376 |
| 0.6882 | 2.0 | 253 | 0.6129 | 0.7874 |
| 0.4068 | 3.0 | 380 | 0.3532 | 0.8876 |
| 0.3587 | 4.0 | 507 | 0.4896 | 0.8622 |
| 0.3013 | 4.99 | 633 | 0.2656 | 0.9078 |
| 0.2777 | 6.0 | 760 | 0.1679 | 0.9472 |
| 0.2093 | 7.0 | 887 | 0.2264 | 0.9302 |
| 0.1866 | 8.0 | 1014 | 0.2245 | 0.9263 |
| 0.1896 | 8.99 | 1140 | 0.2252 | 0.9333 |
| 0.1059 | 10.0 | 1267 | 0.1544 | 0.9528 |
| 0.1072 | 11.0 | 1394 | 0.2232 | 0.9391 |
| 0.1121 | 12.0 | 1521 | 0.1723 | 0.9467 |
| 0.103 | 12.99 | 1647 | 0.1750 | 0.9530 |
| 0.071 | 14.0 | 1774 | 0.1713 | 0.9541 |
| 0.0276 | 15.0 | 1901 | 0.1384 | 0.9631 |
| 0.0279 | 16.0 | 2028 | 0.1575 | 0.9607 |
| 0.0396 | 16.99 | 2154 | 0.1579 | 0.9604 |
| 0.0129 | 18.0 | 2281 | 0.1389 | 0.9674 |
| 0.0031 | 19.0 | 2408 | 0.1315 | 0.9689 |
| 0.0074 | 19.88 | 2520 | 0.1371 | 0.9670 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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