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---
library_name: transformers
license: other
base_model: apple/mobilevit-xx-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_ViT2MobileViT-xx-small
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. -->
# KDRSSC_ViT2MobileViT-xx-small
This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co./apple/mobilevit-xx-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6274
- Accuracy: 0.8495
- Precision: 0.8504
- Recall: 0.8501
- F1: 0.8440
## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6963 | 1.0 | 148 | 1.3476 | 0.596 | 0.6092 | 0.5736 | 0.5557 |
| 1.2335 | 2.0 | 296 | 1.0216 | 0.725 | 0.7180 | 0.7135 | 0.6918 |
| 0.9693 | 3.0 | 444 | 0.8330 | 0.776 | 0.7560 | 0.7699 | 0.7481 |
| 0.8246 | 4.0 | 592 | 0.7345 | 0.812 | 0.8091 | 0.8042 | 0.7889 |
| 0.7393 | 5.0 | 740 | 0.6836 | 0.828 | 0.8084 | 0.8223 | 0.8070 |
| 0.6895 | 6.0 | 888 | 0.6504 | 0.831 | 0.8245 | 0.8253 | 0.8134 |
| 0.6528 | 7.0 | 1036 | 0.6252 | 0.859 | 0.8546 | 0.8571 | 0.8461 |
| 0.6303 | 8.0 | 1184 | 0.6089 | 0.856 | 0.8506 | 0.8554 | 0.8444 |
| 0.6138 | 9.0 | 1332 | 0.6002 | 0.863 | 0.8567 | 0.8632 | 0.8519 |
| 0.6067 | 10.0 | 1480 | 0.6003 | 0.863 | 0.8596 | 0.8624 | 0.8521 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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