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segformer-b0-scene-parse-1502 – AI Model by awaisyaqoob | AlphaNeural AI
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awaisyaqoob
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segformer-b0-scene-parse-1502
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transformers
pytorch
tensorboard
segformer
generated_from_trainer
scene_parse_150
nvidia/mit-b0
finetune
other
endpoints_compatible
us
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segformer-b0-scene-parse-1502
This model is a fine-tuned version of
nvidia/mit-b0
on the scene_parse_150 dataset. It achieves the following results on the evaluation set:
eval_loss: 2.4662
eval_mean_iou: 0.0896
eval_mean_accuracy: 0.1488
eval_overall_accuracy: 0.6372
eval_per_category_iou: [0.49227372671878594, 0.5532565415244596, 0.9483966776020463, 0.4564028097943477, 0.3441962504986039, 0.4576400132036027, 0.5344129222022298, 0.2900375472301515, 0.0, 0.6730487219899952, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
eval_per_category_accuracy: [0.6219459883933374, 0.9121453160561318, 0.9753296111445005, 0.5487499345286939, 0.7937145485206194, 0.9112436777004357, 0.9588236739306685, 0.623475493316359, 0.0, 0.7976902085634462, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]
eval_runtime: 16.2659
eval_samples_per_second: 0.615
eval_steps_per_second: 0.307
epoch: 11.0
step: 220
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
