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---
license: other
tags:
- generated_from_trainer
model-index:
- name: segment_50ep
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. -->
# segment_50ep
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: 0.0867
- eval_mean_iou: 0.8941
- eval_mean_accuracy: 0.9459
- eval_overall_accuracy: 0.9728
- eval_per_category_iou: [0.8914159628180123, 0.9397057910334902, 0.784713695838044, 0.9606094621573129]
- eval_per_category_accuracy: [0.9685998627316403, 0.9696767617484154, 0.8661740631737143, 0.9789942690602516]
- eval_runtime: 40.9902
- eval_samples_per_second: 0.976
- eval_steps_per_second: 0.244
- epoch: 36.82
- step: 3240
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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