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-4-e-15
  results: []
---

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# segformer-b0-scene-parse-150-lr-4-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: 0.1773
- Mean Iou: 0.5116
- Mean Accuracy: 0.5539
- Overall Accuracy: 0.9486
- Per Category Iou: [0.07467818861526594, 0.9484318643687625]
- Per Category Accuracy: [0.13278359055139496, 0.9749314802690082]

## 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: 0.0001
- 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  | 0.3321          | 0.4844   | 0.5000        | 0.9686           | [5.913750483660308e-05, 0.968644931717587]  | [5.9410243004868244e-05, 0.9998514102409571] |
| No log        | 2.0   | 224  | 0.1448          | 0.4844   | 0.5           | 0.9688           | [0.0, 0.9687870873345269]                   | [0.0, 1.0]                                   |
| No log        | 3.0   | 336  | 0.1467          | 0.4855   | 0.5011        | 0.9687           | [0.0024028604839131528, 0.9686745745655791] | [0.002417148172540925, 0.9998084247604243]   |
| No log        | 4.0   | 448  | 0.1597          | 0.4974   | 0.5136        | 0.9673           | [0.02761431295696444, 0.9672534071470754]   | [0.029766229180953417, 0.9974892869900998]   |
| 0.4196        | 5.0   | 560  | 0.1483          | 0.4945   | 0.5101        | 0.9683           | [0.02072799899238894, 0.9682597471616551]   | [0.021509902838791155, 0.9987846484301768]   |
| 0.4196        | 6.0   | 672  | 0.1300          | 0.4973   | 0.5131        | 0.9682           | [0.026546808517533143, 0.9681413453315052]  | [0.02781078346833604, 0.9984659761718246]    |
| 0.4196        | 7.0   | 784  | 0.1407          | 0.5063   | 0.5244        | 0.9659           | [0.04665771796171021, 0.9658509666995633]   | [0.05345563922026602, 0.995305832396877]     |
| 0.4196        | 8.0   | 896  | 0.1377          | 0.5014   | 0.5186        | 0.9662           | [0.036728661127978124, 0.9661516368135028]  | [0.041295211194926705, 0.995994201663374]    |
| 0.174         | 9.0   | 1008 | 0.1632          | 0.5096   | 0.5382        | 0.9570           | [0.06234910880338227, 0.9568704542992275]   | [0.09161908189107895, 0.984874907876537]     |
| 0.174         | 10.0  | 1120 | 0.1424          | 0.5102   | 0.5323        | 0.9627           | [0.05773026579725805, 0.9625824124413115]   | [0.07327829115771892, 0.9913228393342741]    |
| 0.174         | 11.0  | 1232 | 0.1553          | 0.5035   | 0.5223        | 0.9644           | [0.04268206669259935, 0.9643468862627879]   | [0.05084668083459509, 0.9938369430563793]    |
| 0.174         | 12.0  | 1344 | 0.1607          | 0.5086   | 0.5330        | 0.9600           | [0.057171934641356385, 0.95994904570909]    | [0.07762033120361757, 0.9884765551939039]    |
| 0.174         | 13.0  | 1456 | 0.1619          | 0.5095   | 0.5358        | 0.9589           | [0.060308850859297915, 0.958769171435925]   | [0.08455435528004292, 0.9870474246884537]    |
| 0.1457        | 14.0  | 1568 | 0.1625          | 0.5123   | 0.5476        | 0.9534           | [0.07133326653200926, 0.9531840662639103]   | [0.11479756384054969, 0.9803688154229716]    |
| 0.1457        | 15.0  | 1680 | 0.1773          | 0.5116   | 0.5539        | 0.9486           | [0.07467818861526594, 0.9484318643687625]   | [0.13278359055139496, 0.9749314802690082]    |


### Framework versions

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