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-3-e-15
  results: []
---

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# segformer-b0-scene-parse-150-lr-3-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: 0.1523
- Mean Iou: 0.5014
- Mean Accuracy: 0.5220
- Overall Accuracy: 0.9615
- Per Category Iou: [0.04132646470292031, 0.9614038983247747]
- Per Category Accuracy: [0.053216300812732126, 0.9907305584765508]

## 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: 0.001
- 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  | 0.1629          | 0.4844   | 0.5           | 0.9688           | [0.0, 0.9687870873345269]                   | [0.0, 1.0]                                   |
| No log        | 2.0   | 224  | 0.1437          | 0.4844   | 0.5000        | 0.9688           | [2.03629353850122e-05, 0.968778060560053]   | [2.0369226173097684e-05, 0.9999900466190115] |
| No log        | 3.0   | 336  | 0.1551          | 0.4844   | 0.5           | 0.9688           | [0.0, 0.9687870873345269]                   | [0.0, 1.0]                                   |
| No log        | 4.0   | 448  | 0.1536          | 0.4873   | 0.5029        | 0.9674           | [0.0072237010873418455, 0.967349403560223]  | [0.0076096034111664095, 0.998278830733678]   |
| 0.254         | 5.0   | 560  | 0.1730          | 0.4844   | 0.5000        | 0.9688           | [1.697363485298286e-06, 0.9687858141149847] | [1.697435514424807e-06, 0.9999986327773367]  |
| 0.254         | 6.0   | 672  | 0.1726          | 0.4844   | 0.5000        | 0.9688           | [0.0, 0.9687868224249946]                   | [0.0, 0.9999997265554673]                    |
| 0.254         | 7.0   | 784  | 0.1418          | 0.4886   | 0.5042        | 0.9679           | [0.009270700532836455, 0.9678754695078028]  | [0.009627854237817505, 0.998758780577388]    |
| 0.254         | 8.0   | 896  | 0.1618          | 0.4844   | 0.5           | 0.9688           | [0.0, 0.9687870873345269]                   | [0.0, 1.0]                                   |
| 0.2012        | 9.0   | 1008 | 0.1350          | 0.4868   | 0.5023        | 0.9685           | [0.005035086692148778, 0.9684816005292253]  | [0.005109280898418669, 0.9995252456024103]   |
| 0.2012        | 10.0  | 1120 | 0.1429          | 0.4975   | 0.5137        | 0.9673           | [0.027791805303191197, 0.967227089869692]   | [0.02998689579782864, 0.997455270490238]     |
| 0.2012        | 11.0  | 1232 | 0.1419          | 0.4852   | 0.5008        | 0.9688           | [0.0015964088435281823, 0.9688182225729328] | [0.0015972868190737434, 0.9999822807942842]  |
| 0.2012        | 12.0  | 1344 | 0.1339          | 0.4872   | 0.5028        | 0.9686           | [0.00582435621561196, 0.968612834428971]    | [0.00589010123505408, 0.9996363187715734]    |
| 0.2012        | 13.0  | 1456 | 0.1422          | 0.4990   | 0.5165        | 0.9652           | [0.03289244256624029, 0.9651360857253766]   | [0.03794447348945214, 0.9950514742926044]    |
| 0.1837        | 14.0  | 1568 | 0.1423          | 0.4928   | 0.5087        | 0.9673           | [0.01828545458590366, 0.9672482875211772]   | [0.019532390464486255, 0.9978029278690511]   |
| 0.1837        | 15.0  | 1680 | 0.1523          | 0.5014   | 0.5220        | 0.9615           | [0.04132646470292031, 0.9614038983247747]   | [0.053216300812732126, 0.9907305584765508]   |


### Framework versions

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