---
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch32-finetuned-eurosat
  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. -->

# clip-vit-base-patch32-finetuned-eurosat

This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0987
- Accuracy: 0.9716

## 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: 5e-05
- 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4295        | 0.9979 | 351  | 0.2629          | 0.915    |
| 0.4167        | 1.9986 | 703  | 0.2365          | 0.9222   |
| 0.4104        | 2.9993 | 1055 | 0.2205          | 0.9252   |
| 0.3847        | 4.0    | 1407 | 0.1917          | 0.9338   |
| 0.3928        | 4.9979 | 1758 | 0.1803          | 0.9414   |
| 0.311         | 5.9986 | 2110 | 0.1429          | 0.9524   |
| 0.2614        | 6.9993 | 2462 | 0.1137          | 0.961    |
| 0.2579        | 8.0    | 2814 | 0.1102          | 0.9638   |
| 0.1993        | 8.9979 | 3165 | 0.1037          | 0.9688   |
| 0.1921        | 9.9787 | 3510 | 0.0987          | 0.9716   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1