mraottth/trashbot_v1

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: 0.0191
• Mean Iou: 0.3997
• Mean Accuracy: 0.7995
• Overall Accuracy: 0.7995
• Accuracy Unlabeled: nan
• Accuracy Trash: 0.7995
• Iou Unlabeled: 0.0
• Iou Trash: 0.7995

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 Unlabeled	Iou Trash
0.0748	1.0	90	0.0386	0.3630	0.7259	0.7259	nan	0.7259	0.0	0.7259
0.039	2.0	180	0.0242	0.3803	0.7607	0.7607	nan	0.7607	0.0	0.7607
0.0194	3.0	270	0.0242	0.3605	0.7210	0.7210	nan	0.7210	0.0	0.7210
0.0112	4.0	360	0.0205	0.3995	0.7991	0.7991	nan	0.7991	0.0	0.7991
0.0169	5.0	450	0.0192	0.4000	0.8000	0.8000	nan	0.8000	0.0	0.8000
0.041	6.0	540	0.0196	0.3838	0.7677	0.7677	nan	0.7677	0.0	0.7677
0.0188	7.0	630	0.0191	0.4139	0.8277	0.8277	nan	0.8277	0.0	0.8277
0.0073	8.0	720	0.0190	0.4069	0.8138	0.8138	nan	0.8138	0.0	0.8138
0.025	9.0	810	0.0191	0.4087	0.8174	0.8174	nan	0.8174	0.0	0.8174
0.006	10.0	900	0.0191	0.3997	0.7995	0.7995	nan	0.7995	0.0	0.7995

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2