---
license: other
tags:
- generated_from_trainer
model-index:
- name: deprem_satellite_semantic_xview2_large_2
  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. -->

# deprem_satellite_semantic_xview2_large_2

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9892
- eval_mean_iou: 0.3093
- eval_mean_accuracy: 0.3576
- eval_overall_accuracy: 0.9646
- eval_accuracy_background: 0.9860
- eval_accuracy_nodamage: 0.8022
- eval_accuracy_minordamaged: 0.0
- eval_accuracy_majordamaged: 0.0
- eval_accuracy_destroyed: 0.0
- eval_iou_background: 0.9677
- eval_iou_nodamage: 0.5789
- eval_iou_minordamaged: 0.0
- eval_iou_majordamaged: 0.0
- eval_iou_destroyed: 0.0
- eval_runtime: 200.8095
- eval_samples_per_second: 4.646
- eval_steps_per_second: 4.646
- epoch: 19.3
- step: 27000

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2