transformers safetensors segformer generated_from_trainer base_model:nvidia/mit-b0 license:other endpoints_compatible region:us
---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_trainer
model-index:
- name: segformer-test
  results: []
---

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# segformer-test

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3699
- eval_mean_iou: 0.5261
- eval_mean_accuracy: 0.6103
- eval_overall_accuracy: 0.9163
- eval_per_category_iou: [0.6440921586675343, 0.7803556002366734, 0.2939456425332648, 0.21142047034966666, 0.38076799132467504, 0.517520127105597, 0.8584623722607826, 0.9583354624978893, 0.1412645399055626, 0.12232558139534884, 0.8788054295225798, nan]
- eval_per_category_accuracy: [0.8187515502058933, 0.9113968634790757, 0.31292325038191526, 0.24646864879791802, 0.4941417789077488, 0.6124207890888539, 0.9331841161885152, 0.9812724610884527, 0.17548427708947323, 0.2838640043173233, 0.9429806974946743, nan]
- eval_runtime: 344.8194
- eval_samples_per_second: 1.351
- eval_steps_per_second: 0.676
- epoch: 6.16
- step: 6760

## 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: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2
