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---
license: other
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: mobilenet_v1_0.75_192-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.3103448275862069
---
<!-- 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. -->
# mobilenet_v1_0.75_192-finetuned-eurosat
This model is a fine-tuned version of [google/mobilenet_v1_0.75_192](https://huggingface.co/google/mobilenet_v1_0.75_192) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3344
- Accuracy: 0.3103
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3566 | 1.0 | 65 | 1.3639 | 0.3103 |
| 0.9354 | 2.0 | 130 | 1.4389 | 0.2759 |
| 0.8786 | 3.0 | 195 | 1.3344 | 0.3103 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.3
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