earthquake

This model is a fine-tuned version of nvidia/mit-b0 on the gokceKy/earthquake dataset. It achieves the following results on the evaluation set:

• Loss: 1.6395
• Mean Iou: 0.1763
• Mean Accuracy: 0.4255
• Overall Accuracy: 0.6211
• Accuracy Background: nan
• Accuracy Car: nan
• Accuracy Earthquake-roads: 0.4591
• Accuracy Other: 0.8175
• Accuracy Road: 0.0
• Accuracy Road-cracks: nan
• Accuracy Sky: nan
• Accuracy Wall: nan
• Iou Background: 0.0
• Iou Car: 0.0
• Iou Earthquake-roads: 0.4499
• Iou Other: 0.7841
• Iou Road: 0.0
• Iou Road-cracks: 0.0
• Iou Sky: 0.0
• Iou Wall: nan

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Background	Accuracy Car	Accuracy Earthquake-roads	Accuracy Other	Accuracy Road	Accuracy Road-cracks	Accuracy Sky	Accuracy Wall	Iou Background	Iou Car	Iou Earthquake-roads	Iou Other	Iou Road	Iou Road-cracks	Iou Sky	Iou Wall
1.0736	2.5	5	1.6917	0.1818	0.3763	0.5984	nan	nan	0.3113	0.8176	0.0	nan	nan	nan	0.0	0.0	0.3077	0.7830	0.0	0.0	nan	nan
0.8949	5.0	10	1.6395	0.1763	0.4255	0.6211	nan	nan	0.4591	0.8175	0.0	nan	nan	nan	0.0	0.0	0.4499	0.7841	0.0	0.0	0.0	nan

Framework versions

• Transformers 4.46.2
• Pytorch 2.4.1+cpu
• Datasets 3.1.0
• Tokenizers 0.20.3