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README.md
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---
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license: other
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base_model: nvidia/segformer-b0-finetuned-ade-512-512
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: segformer-proposed-5
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7089344469754493
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# segformer-proposed-5
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This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8378
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- Accuracy: 0.7089
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 5.9051 | 1.0 | 247 | 5.0387 | 0.0597 |
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| 4.644 | 2.0 | 494 | 3.3368 | 0.3475 |
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| 3.4264 | 3.0 | 741 | 2.4415 | 0.5804 |
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| 3.0112 | 4.0 | 988 | 2.0148 | 0.6760 |
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| 2.6763 | 5.0 | 1235 | 1.8378 | 0.7089 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.2+cu121
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- Datasets 3.0.0
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- Tokenizers 0.15.2
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