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---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-oldapp-oct-1
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. -->
# segformer-b0-finetuned-oldapp-oct-1
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the PushkarA07/oldapptiles5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2630
- Mean Iou: 0.4984
- Mean Accuracy: 0.4989
- Overall Accuracy: 0.9967
- Accuracy Abnormality: 0.0
- Iou Abnormality: 0.0
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Abnormality | Iou Abnormality |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------:|:---------------:|
| 0.6912 | 0.7143 | 10 | 0.6575 | 0.4714 | 0.4784 | 0.9426 | 0.0133 | 0.0002 |
| 0.5802 | 1.4286 | 20 | 0.5878 | 0.4942 | 0.4947 | 0.9884 | 0.0 | 0.0 |
| 0.5498 | 2.1429 | 30 | 0.4770 | 0.4984 | 0.4989 | 0.9968 | 0.0 | 0.0 |
| 0.6084 | 2.8571 | 40 | 0.4125 | 0.4971 | 0.4976 | 0.9941 | 0.0 | 0.0 |
| 0.4675 | 3.5714 | 50 | 0.4355 | 0.4885 | 0.4992 | 0.9761 | 0.0213 | 0.0009 |
| 0.3863 | 4.2857 | 60 | 0.3699 | 0.4965 | 0.5005 | 0.9920 | 0.0081 | 0.0010 |
| 0.3954 | 5.0 | 70 | 0.3401 | 0.4983 | 0.4989 | 0.9967 | 0.0 | 0.0 |
| 0.3286 | 5.7143 | 80 | 0.3279 | 0.4983 | 0.4988 | 0.9967 | 0.0 | 0.0 |
| 0.3458 | 6.4286 | 90 | 0.2908 | 0.4974 | 0.4979 | 0.9948 | 0.0 | 0.0 |
| 0.3559 | 7.1429 | 100 | 0.2693 | 0.4989 | 0.4994 | 0.9978 | 0.0 | 0.0 |
| 0.3196 | 7.8571 | 110 | 0.2596 | 0.4977 | 0.4982 | 0.9954 | 0.0 | 0.0 |
| 0.3109 | 8.5714 | 120 | 0.2915 | 0.4958 | 0.4963 | 0.9916 | 0.0 | 0.0 |
| 0.2711 | 9.2857 | 130 | 0.2720 | 0.4991 | 0.4997 | 0.9983 | 0.0 | 0.0 |
| 0.3051 | 10.0 | 140 | 0.2630 | 0.4984 | 0.4989 | 0.9967 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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