transformers tensorboard safetensors segformer generated_from_trainer base_model:klentree/segformer-b0-scene-parse-150-20 license:openrail endpoints_compatible region:us
---
license: openrail
base_model: klentree/segformer-b0-scene-parse-150-20
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-scene-parse-150-50
  results: []
---

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# segformer-b0-scene-parse-150-50

This model is a fine-tuned version of [klentree/segformer-b0-scene-parse-150-20](https://huggingface.co/klentree/segformer-b0-scene-parse-150-20) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9992
- Mean Iou: 0.1414
- Mean Accuracy: 0.5623
- Overall Accuracy: 0.2681
- Per Category Iou: [0.03415709043952773, 0.2486167920519975]
- Per Category Accuracy: [0.8749923648579864, 0.24956422933712585]

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                             | Per Category Accuracy                      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------------------------------:|:------------------------------------------:|
| No log        | 1.0   | 133  | 1.3809          | 0.1831   | 0.6100        | 0.3452           | [0.038710505981588275, 0.3274145847863719]   | [0.8914028300926398, 0.32849851170741207]  |
| No log        | 2.0   | 266  | 3.1399          | 0.0278   | 0.5071        | 0.0541           | [0.02998980464207664, 0.02561876180112447]   | [0.9885405001866368, 0.025627711476269972] |
| No log        | 3.0   | 399  | 1.4873          | 0.1612   | 0.5930        | 0.3045           | [0.036857115032605504, 0.28551314243518766]  | [0.8996386032780209, 0.28638666931766954]  |
| 0.131         | 4.0   | 532  | 1.8598          | 0.0884   | 0.5443        | 0.1683           | [0.03248204249077747, 0.14439283966619093]   | [0.9438817061997353, 0.14463986050373331]  |
| 0.131         | 5.0   | 665  | 1.1300          | 0.2009   | 0.6049        | 0.3790           | [0.03869589759308316, 0.3630560542281187]    | [0.8450235841053311, 0.3647712858322449]   |
| 0.131         | 6.0   | 798  | 3.4677          | 0.0281   | 0.5067        | 0.0547           | [0.029968966006210712, 0.026287373046977498] | [0.9871950184940107, 0.02629763451787782]  |
| 0.131         | 7.0   | 931  | 0.8035          | 0.3046   | 0.6395        | 0.5715           | [0.0468379925244376, 0.5622884059713553]     | [0.7117632087956836, 0.567229146162601]    |
| 0.1093        | 8.0   | 1064 | 3.0148          | 0.0372   | 0.5090        | 0.0717           | [0.03010087836424667, 0.04420013882895897]   | [0.9738284298754624, 0.0442354032603611]   |
| 0.1093        | 9.0   | 1197 | 1.3918          | 0.1977   | 0.6147        | 0.3726           | [0.03949337936321034, 0.35595848950467285]   | [0.8720570769282975, 0.35734683993080635]  |
| 0.1093        | 10.0  | 1330 | 0.8904          | 0.3048   | 0.6555        | 0.5705           | [0.04885666809307599, 0.5607852599315016]    | [0.7458023685907225, 0.5651308780936614]   |
| 0.1093        | 11.0  | 1463 | 2.1101          | 0.1091   | 0.5544        | 0.2072           | [0.03330984189332642, 0.18492787307291492]   | [0.9234432793783298, 0.18535946088367358]  |
| 0.0978        | 12.0  | 1596 | 0.3487          | 0.4522   | 0.6510        | 0.8320           | [0.07471728817756591, 0.8296494449285194]    | [0.4586853982150735, 0.8433402139408958]   |
| 0.0978        | 13.0  | 1729 | 1.0341          | 0.2902   | 0.6500        | 0.5437           | [0.0471396698931736, 0.5331783341429923]     | [0.7630459126539754, 0.5370297478519739]   |
| 0.0978        | 14.0  | 1862 | 8.8510          | 0.0191   | 0.5026        | 0.0378           | [0.029729543963973613, 0.008555530995168384] | [0.9966099969459432, 0.008556415154495053] |
| 0.0978        | 15.0  | 1995 | 1.5468          | 0.2099   | 0.6104        | 0.3958           | [0.039432935991880434, 0.38042719301704037]  | [0.8384437883877973, 0.38230080082492807]  |
| 0.0938        | 16.0  | 2128 | 0.3316          | 0.4622   | 0.6499        | 0.8478           | [0.07871638020749482, 0.8457624711227079]    | [0.43967728799755673, 0.8602092195727595]  |
| 0.0938        | 17.0  | 2261 | 6.8985          | 0.0200   | 0.5030        | 0.0394           | [0.02975190949797357, 0.010246433961607446]  | [0.9957090501883336, 0.01024777428517577]  |
| 0.0938        | 18.0  | 2394 | 3.6067          | 0.0460   | 0.5068        | 0.0885           | [0.02995386117285437, 0.06208246891194747]   | [0.9514455868879161, 0.062174361643823145] |
| 0.092         | 19.0  | 2527 | 0.2255          | 0.4956   | 0.6091        | 0.9069           | [0.08506947955817622, 0.9060937507594746]    | [0.29259221554854253, 0.9256338355411345]  |
| 0.092         | 20.0  | 2660 | 1.9992          | 0.1414   | 0.5623        | 0.2681           | [0.03415709043952773, 0.2486167920519975]    | [0.8749923648579864, 0.24956422933712585]  |


### Framework versions

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