transformers tensorboard safetensors mobilevitv2 image-classification generated_from_trainer base_model:apple/mobilevitv2-1.0-imagenet1k-256 license:other autotrain_compatible endpoints_compatible region:us
---
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
