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mraottth/
trashbot

Name: trashbot
Availability: InStock

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trashbot

This model is a fine-tuned version of nvidia/mit-b5 on the mraottth/all_locations_pooled dataset. It achieves the following results on the evaluation set:

Loss: 0.0189
Mean Iou: 0.4050
Mean Accuracy: 0.8101
Overall Accuracy: 0.8101
Accuracy Unlabeled: nan
Accuracy Trash: 0.8101
Iou Unlabeled: 0.0
Iou Trash: 0.8101

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: 3
eval_batch_size: 3
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Trash	Iou Trash
0.0592	1.0	90	0.0387	0.3723	0.7446	0.7446	nan	0.7446	0.7446
0.0402	2.0	180	0.0281	0.4123	0.8247	0.8247	nan	0.8247	0.8247
0.0209	3.0	270	0.0246	0.3691	0.7382	0.7382	nan	0.7382	0.7382
0.0117	4.0	360	0.0210	0.3882	0.7763	0.7763	nan	0.7763	0.7763
0.019	5.0	450	0.0198	0.3822	0.7644	0.7644	nan	0.7644	0.7644
0.0445	6.0	540	0.0199	0.3771	0.7542	0.7542	nan	0.7542	0.7542
0.0195	7.0	630	0.0191	0.4177	0.8354	0.8354	nan	0.8354	0.8354
0.008	8.0	720	0.0191	0.4060	0.8119	0.8119	nan	0.8119	0.8119
0.0268	9.0	810	0.0188	0.4083	0.8166	0.8166	nan	0.8166	0.8166
0.0061	10.0	900	0.0189	0.4050	0.8101	0.8101	nan	0.8101	0.8101

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2

mraottth/trashbot

trashbot

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mraottth/
trashbot