---
license: other
tags:
- generated_from_trainer
base_model: nvidia/mit-b0
model-index:
- name: Aerial-Drone-Image-Segmentation
  results: []
pipeline_tag: image-segmentation
---

<!-- 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. -->

# Aerial-Drone-Image-Segmentation

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0)
It achieves the following results on the evaluation set:
- Loss: 0.8852
- Mean Iou: 0.2994
- Mean Accuracy: 0.3923
- Overall Accuracy: 0.7774

## Model description

More information needed


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64fec5de57ccb8f1bdfbec54/nRUHIJAj52l3wxMTJARka.png)

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|
| 2.7923        | 1.25  | 20   | 2.8338          | 0.0954   | 0.1626        | 0.5529           |
| 2.219         | 2.5   | 40   | 2.1391          | 0.1036   | 0.1666        | 0.5929           |
| 1.9451        | 3.75  | 60   | 1.7919          | 0.1154   | 0.1782        | 0.6129           |
| 1.7558        | 5.0   | 80   | 1.6767          | 0.1300   | 0.1961        | 0.6396           |
| 1.6381        | 6.25  | 100  | 1.5817          | 0.1383   | 0.2055        | 0.6550           |
| 1.5338        | 7.5   | 120  | 1.4816          | 0.1464   | 0.2140        | 0.6729           |
| 1.4478        | 8.75  | 140  | 1.4231          | 0.1529   | 0.2219        | 0.6823           |
| 1.361         | 10.0  | 160  | 1.3300          | 0.1637   | 0.2315        | 0.6975           |
| 1.306         | 11.25 | 180  | 1.3034          | 0.1737   | 0.2419        | 0.7060           |
| 1.2611        | 12.5  | 200  | 1.2692          | 0.1755   | 0.2450        | 0.7093           |
| 1.2317        | 13.75 | 220  | 1.2190          | 0.1821   | 0.2501        | 0.7145           |
| 1.1868        | 15.0  | 240  | 1.2063          | 0.1862   | 0.2539        | 0.7188           |
| 1.1628        | 16.25 | 260  | 1.1832          | 0.1909   | 0.2612        | 0.7234           |
| 1.1149        | 17.5  | 280  | 1.1368          | 0.2048   | 0.2739        | 0.7317           |
| 1.1009        | 18.75 | 300  | 1.1117          | 0.2232   | 0.2938        | 0.7387           |
| 1.0532        | 20.0  | 320  | 1.0923          | 0.2315   | 0.2997        | 0.7414           |
| 1.0464        | 21.25 | 340  | 1.0821          | 0.2408   | 0.3147        | 0.7480           |
| 1.0278        | 22.5  | 360  | 1.0541          | 0.2517   | 0.3277        | 0.7530           |
| 0.9945        | 23.75 | 380  | 1.0352          | 0.2612   | 0.3398        | 0.7573           |
| 0.9729        | 25.0  | 400  | 1.0207          | 0.2671   | 0.3511        | 0.7609           |
| 0.9527        | 26.25 | 420  | 1.0067          | 0.2684   | 0.3547        | 0.7609           |
| 0.9494        | 27.5  | 440  | 0.9870          | 0.2713   | 0.3548        | 0.7627           |
| 0.9287        | 28.75 | 460  | 0.9729          | 0.2745   | 0.3619        | 0.7640           |
| 0.9089        | 30.0  | 480  | 0.9561          | 0.2791   | 0.3640        | 0.7680           |
| 0.9064        | 31.25 | 500  | 0.9500          | 0.2799   | 0.3712        | 0.7672           |
| 0.8681        | 32.5  | 520  | 0.9397          | 0.2845   | 0.3749        | 0.7696           |
| 0.8677        | 33.75 | 540  | 0.9340          | 0.2835   | 0.3737        | 0.7692           |
| 0.8663        | 35.0  | 560  | 0.9243          | 0.2862   | 0.3755        | 0.7716           |
| 0.8629        | 36.25 | 580  | 0.9173          | 0.2869   | 0.3766        | 0.7719           |
| 0.8542        | 37.5  | 600  | 0.9112          | 0.2908   | 0.3810        | 0.7740           |
| 0.8391        | 38.75 | 620  | 0.9050          | 0.2904   | 0.3812        | 0.7734           |
| 0.8392        | 40.0  | 640  | 0.9027          | 0.2917   | 0.3818        | 0.7734           |
| 0.8306        | 41.25 | 660  | 0.8949          | 0.2941   | 0.3841        | 0.7755           |
| 0.8213        | 42.5  | 680  | 0.8936          | 0.2958   | 0.3875        | 0.7760           |
| 0.8406        | 43.75 | 700  | 0.8910          | 0.2964   | 0.3879        | 0.7763           |
| 0.8254        | 45.0  | 720  | 0.8889          | 0.2981   | 0.3897        | 0.7764           |
| 0.8202        | 46.25 | 740  | 0.8880          | 0.2985   | 0.3917        | 0.7767           |
| 0.8013        | 47.5  | 760  | 0.8891          | 0.2989   | 0.3923        | 0.7767           |
| 0.8188        | 48.75 | 780  | 0.8861          | 0.2994   | 0.3926        | 0.7772           |
| 0.8089        | 50.0  | 800  | 0.8852          | 0.2994   | 0.3923        | 0.7774           |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2