Model save

README.md

@@ -15,62 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # SegFormer_b2_mappillary_
 
 This model is a fine-tuned version of [nvidia/segformer-b2-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b2-finetuned-cityscapes-1024-1024) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- epoch: 7.1111
-- eval_accuracy_construction--barrier--fence: 0.6884
-- eval_accuracy_construction--barrier--guard-rail: 0.8285
-- eval_accuracy_construction--barrier--other-barrier: 0.6796
-- eval_accuracy_construction--barrier--wall: 0.6617
-- eval_accuracy_construction--flat--road: 0.9450
-- eval_accuracy_construction--flat--service-lane: 0.6045
-- eval_accuracy_construction--flat--sidewalk: 0.9036
-- eval_accuracy_construction--structure--building: 0.9448
-- eval_accuracy_human--person: 0.8152
-- eval_accuracy_human--rider--bicyclist: 0.7298
-- eval_accuracy_marking--crosswalk-zebra: 0.8040
-- eval_accuracy_marking--general: 0.6630
-- eval_accuracy_nature--sky: 0.9894
-- eval_accuracy_nature--terrain: 0.7920
-- eval_accuracy_nature--vegetation: 0.9467
-- eval_accuracy_object--support--pole: 0.5267
-- eval_accuracy_object--support--traffic-sign-frame: 0.6493
-- eval_accuracy_object--traffic-light: 0.7177
-- eval_accuracy_object--traffic-sign--front: 0.7995
-- eval_accuracy_object--vehicle--bicycle: 0.7409
-- eval_accuracy_object--vehicle--bus: 0.8505
-- eval_accuracy_object--vehicle--car: 0.9596
-- eval_accuracy_object--vehicle--truck: 0.7913
-- eval_iou_construction--barrier--fence: 0.5326
-- eval_iou_construction--barrier--guard-rail: 0.6142
-- eval_iou_construction--barrier--other-barrier: 0.5604
-- eval_iou_construction--barrier--wall: 0.5195
-- eval_iou_construction--flat--road: 0.9074
-- eval_iou_construction--flat--service-lane: 0.4444
-- eval_iou_construction--flat--sidewalk: 0.7564
-- eval_iou_construction--structure--building: 0.8785
-- eval_iou_human--person: 0.6633
-- eval_iou_human--rider--bicyclist: 0.5386
-- eval_iou_marking--crosswalk-zebra: 0.6628
-- eval_iou_marking--general: 0.5555
-- eval_iou_nature--sky: 0.9801
-- eval_iou_nature--terrain: 0.6805
-- eval_iou_nature--vegetation: 0.8897
-- eval_iou_object--support--pole: 0.4260
-- eval_iou_object--support--traffic-sign-frame: 0.5314
-- eval_iou_object--traffic-light: 0.5586
-- eval_iou_object--traffic-sign--front: 0.6967
-- eval_iou_object--vehicle--bicycle: 0.5583
-- eval_iou_object--vehicle--bus: 0.7226
-- eval_iou_object--vehicle--car: 0.8913
-- eval_iou_object--vehicle--truck: 0.6813
-- eval_loss: 0.9738
-- eval_mean_accuracy: 0.7840
-- eval_mean_iou: 0.6630
-- eval_overall_accuracy: 0.9356
-- eval_runtime: 1231.0899
-- eval_samples_per_second: 1.625
-- eval_steps_per_second: 0.812
-- step: 16000
 
 ## Model description
 
@@ -89,7 +33,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 9e-05
 - train_batch_size: 2
 - eval_batch_size: 2
 - seed: 42

model.safetensors

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training_args.bin

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