update model card README.md

README.md

@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the reannayang/FL_pavement dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4558
-- Mean Iou: 0.6310
-- Mean Accuracy: 0.7758
-- Overall Accuracy: 0.9687
-- Per Category Iou: [0.0, 0.9582107718835582, 0.9831802335937301, 0.0, 0.9070478290281362, 0.9376628700260592]
-- Per Category Accuracy: [nan, 0.964865692983352, 0.9920279343235298, 0.0, 0.9513585956798234, 0.9709244156080405]
+- Loss: 0.4165
+- Mean Iou: 0.6318
+- Mean Accuracy: 0.9700
+- Overall Accuracy: 0.9738
+- Per Category Iou: [0.0, 0.964166382973358, 0.9809231860559384, 0.0, 0.9295139919583345, 0.9164463823409184]
+- Per Category Accuracy: [nan, 0.9643001261034048, 0.9983497924348297, nan, 0.995031342981772, 0.9223532638507954]
 
 ## Model description
 
@@ -52,16 +52,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                                                                           | Per Category Accuracy                                                                      |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------:|
-| 1.0751        | 10.0  | 20   | 1.1494          | 0.5858   | 0.7574        | 0.9436           | [0.0, 0.9446293533289976, 0.9477727359877293, 0.0, 0.7979866954491387, 0.8246812143200128] | [nan, 0.9457026861403329, 0.951885181714315, 0.0, 0.9519892783938614, 0.93727071521693]    |
-| 0.8732        | 20.0  | 40   | 0.6625          | 0.6209   | 0.7710        | 0.9635           | [0.0, 0.9549288283268325, 0.9793625315294657, 0.0, 0.8879129036248917, 0.903449846293977]  | [nan, 0.9626825656214891, 0.9869186233102687, 0.0, 0.9430020497188206, 0.9623139192917564] |
-| 0.4736        | 30.0  | 60   | 0.5124          | 0.6302   | 0.7753        | 0.9687           | [0.0, 0.9600678403726158, 0.9813250559739467, 0.0, 0.9086066088704611, 0.9311320479537963] | [nan, 0.968414870799714, 0.990282039102918, 0.0, 0.9501760655910022, 0.9678319134099385]   |
-| 0.503         | 40.0  | 80   | 0.4726          | 0.6305   | 0.7753        | 0.9680           | [0.0, 0.9574198453934862, 0.9821685397548652, 0.0, 0.9074944966980188, 0.9358034824412265] | [nan, 0.9645337554897355, 0.9906414881189263, 0.0, 0.953329479161192, 0.9678925507079404]  |
-| 0.6762        | 50.0  | 100  | 0.4558          | 0.6310   | 0.7758        | 0.9687           | [0.0, 0.9582107718835582, 0.9831802335937301, 0.0, 0.9070478290281362, 0.9376628700260592] | [nan, 0.964865692983352, 0.9920279343235298, 0.0, 0.9513585956798234, 0.9709244156080405]  |
+| 1.0651        | 10.0  | 20   | 1.3005          | 0.5967   | 0.9512        | 0.9534           | [0.0, 0.9462421185372005, 0.9681701711239586, 0.0, 0.7994398965962947, 0.8662896799897185] | [nan, 0.9462421185372005, 0.9693809143181291, nan, 0.9648149753011526, 0.9243828853538124] |
+| 0.5732        | 20.0  | 40   | 0.6626          | 0.6287   | 0.9702        | 0.9760           | [0.0, 0.975246652572234, 0.985446932366533, 0.0, 0.9010974339804011, 0.9103918683964157]   | [nan, 0.9772635561160151, 0.9952040842637238, nan, 0.9748678395008233, 0.9334887547997806] |
+| 0.6987        | 30.0  | 60   | 0.4319          | 0.6317   | 0.9705        | 0.9758           | [0.0, 0.9709705045212967, 0.9798115236227942, 0.0, 0.9255918522130127, 0.9139245313729214] | [nan, 0.9722194199243379, 0.9986205296134905, nan, 0.9871161568015715, 0.924026330224904]  |
+| 0.6915        | 40.0  | 80   | 0.4382          | 0.6237   | 0.9634        | 0.9692           | [0.0, 0.9611727616645649, 0.9725125142706595, 0.0, 0.9147983251179308, 0.8937433316006894] | [nan, 0.9611727616645649, 0.9993811721630611, nan, 0.9971690210012422, 0.896023038946791]  |
+| 0.4373        | 50.0  | 100  | 0.4165          | 0.6318   | 0.9700        | 0.9738           | [0.0, 0.964166382973358, 0.9809231860559384, 0.0, 0.9295139919583345, 0.9164463823409184]  | [nan, 0.9643001261034048, 0.9983497924348297, nan, 0.995031342981772, 0.9223532638507954]  |
 
 
 ### Framework versions
 
 - Transformers 4.19.2
-- Pytorch 1.11.0+cu113
-- Datasets 2.2.2
+- Pytorch 1.7.1
+- Datasets 2.2.1
 - Tokenizers 0.12.1