transformers tensorboard safetensors segformer generated_from_trainer base_model:DiTo97/binarization-segformer-b3 license:openrail endpoints_compatible region:us
---
license: openrail
base_model: DiTo97/binarization-segformer-b3
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-scene-parse-150-lr-5-e-15
  results: []
---

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# segformer-b0-scene-parse-150-lr-5-e-15

This model is a fine-tuned version of [DiTo97/binarization-segformer-b3](https://huggingface.co/DiTo97/binarization-segformer-b3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2657
- Mean Iou: 0.4845
- Mean Accuracy: 0.5001
- Overall Accuracy: 0.9672
- Per Category Iou: [0.0018194025597222916, 0.9671517415294609]
- Per Category Accuracy: [0.001918102131300032, 0.9982521972361976]

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                            | Per Category Accuracy                       |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------------------------------:|:-------------------------------------------:|
| No log        | 1.0   | 112  | 2.2288          | 0.0208   | 0.4868        | 0.0410           | [0.03036636790421317, 0.011265774627153866] | [0.9622473367236779, 0.011279477594064372]  |
| No log        | 2.0   | 224  | 1.6154          | 0.0182   | 0.4963        | 0.0362           | [0.03097736523913424, 0.005513312495278201] | [0.9871504131558042, 0.005515594979208372]  |
| No log        | 3.0   | 336  | 0.9216          | 0.1937   | 0.5158        | 0.3688           | [0.032185306965168796, 0.3552501717296959]  | [0.672525648250623, 0.3589983267382158]     |
| No log        | 4.0   | 448  | 0.9276          | 0.1561   | 0.5134        | 0.2969           | [0.03198740212709094, 0.280147471502915]    | [0.7443848833182828, 0.28245463938025656]   |
| 1.4322        | 5.0   | 560  | 0.6011          | 0.4362   | 0.5033        | 0.8459           | [0.0271617976460957, 0.8452071385383193]    | [0.13786740991709726, 0.8686841695959868]   |
| 1.4322        | 6.0   | 672  | 0.3566          | 0.4843   | 0.4999        | 0.9653           | [0.003156516583524233, 0.9653443351384307]  | [0.0035153889503737753, 0.9963369917295061] |
| 1.4322        | 7.0   | 784  | 0.4510          | 0.4833   | 0.5026        | 0.9515           | [0.015110478622284323, 0.9514896636755739]  | [0.023826902315981016, 0.981414850138177]   |
| 1.4322        | 8.0   | 896  | 0.3993          | 0.4862   | 0.5025        | 0.9626           | [0.009768906238396621, 0.9625427377471698]  | [0.011834520406569755, 0.9931874576024252]  |
| 0.4808        | 9.0   | 1008 | 0.3568          | 0.4846   | 0.5002        | 0.9663           | [0.002888368095508705, 0.9662512532108187]  | [0.003131768524113769, 0.9972849692353025]  |
| 0.4808        | 10.0  | 1120 | 0.3781          | 0.4844   | 0.5001        | 0.9654           | [0.0034702934336066026, 0.9653985402997675] | [0.003859968359802011, 0.9963822194552067]  |
| 0.4808        | 11.0  | 1232 | 0.3318          | 0.4845   | 0.5001        | 0.9665           | [0.0024548211803361556, 0.9665399129138876] | [0.00263781478941615, 0.9975982819808147]   |
| 0.4808        | 12.0  | 1344 | 0.3552          | 0.4849   | 0.5005        | 0.9664           | [0.0033778104561300974, 0.9663867278345344] | [0.003649486356013335, 0.9974086755418741]  |
| 0.4808        | 13.0  | 1456 | 0.2612          | 0.4845   | 0.5001        | 0.9672           | [0.0017608302346806158, 0.9671985933973519] | [0.0018535995817518893, 0.9983025657191121] |
| 0.3392        | 14.0  | 1568 | 0.2300          | 0.4845   | 0.5001        | 0.9671           | [0.0018163185523506766, 0.9671249858066228] | [0.001916404695785607, 0.9982246340273064]  |
| 0.3392        | 15.0  | 1680 | 0.2657          | 0.4845   | 0.5001        | 0.9672           | [0.0018194025597222916, 0.9671517415294609] | [0.001918102131300032, 0.9982521972361976]  |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
