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greenkwd/
lr0.0001_bs16_0613_1406

Name: lr0.0001_bs16_0613_1406
Availability: InStock

generated_from_trainer

nvidia/mit-b0

finetune

other

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lr0.0001_bs16_0613_1406

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

Loss: 0.2475
Mean Iou: 0.5250
Mean Accuracy: 0.8644
Overall Accuracy: 0.8974
Accuracy Land: nan
Accuracy Upwelling: 0.9447
Accuracy Not Upwelling: 0.7842
Iou Land: 0.0
Iou Upwelling: 0.8812
Iou Not Upwelling: 0.6937
Dice Macro: 0.9072
Dice Micro: 0.9350

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Land	Accuracy Upwelling	Accuracy Not Upwelling	Iou Upwelling	Iou Not Upwelling	Dice Macro	Dice Micro
0.9564	10.0	20	1.0348	0.3708	0.7051	0.7459	nan	0.8044	0.6058	0.6974	0.4150	0.6938	0.7353
0.7616	20.0	40	0.8405	0.4019	0.7384	0.7810	nan	0.8422	0.6346	0.7402	0.4655	0.7633	0.8127
0.6029	30.0	60	0.5523	0.4551	0.7901	0.8384	nan	0.9077	0.6725	0.8092	0.5561	0.8294	0.8753
0.4617	40.0	80	0.4134	0.4867	0.8413	0.8640	nan	0.8966	0.7859	0.8289	0.6311	0.8586	0.8934
0.434	50.0	100	0.3439	0.4928	0.8247	0.8760	nan	0.9496	0.6998	0.8534	0.6250	0.8750	0.9132
0.3962	60.0	120	0.3170	0.5029	0.8547	0.8784	nan	0.9125	0.7970	0.8492	0.6593	0.8833	0.9145
0.3269	70.0	140	0.2858	0.5009	0.8345	0.8798	nan	0.9447	0.7243	0.8623	0.6404	0.8874	0.9220
0.3104	80.0	160	0.2693	0.5131	0.8535	0.8893	nan	0.9409	0.7661	0.8677	0.6717	0.8960	0.9267
0.2788	90.0	180	0.2553	0.5210	0.8605	0.8971	nan	0.9497	0.7713	0.8738	0.6891	0.8998	0.9293
0.3077	100.0	200	0.2475	0.5250	0.8644	0.8974	nan	0.9447	0.7842	0.8812	0.6937	0.9072	0.9350

Framework versions

Transformers 4.41.2
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.19.1

greenkwd/lr0.0001_bs16_0613_1406

lr0.0001_bs16_0613_1406

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

greenkwd/
lr0.0001_bs16_0613_1406