best_model.pt

README.md

@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Model Preparation Time: 0.0011
-- Accuracy: 0.9858
-- F1: 0.9827
-- Iou: 0.9720
-- Contour Dice: 0.9854
-- Per Class Metrics: {0: {'f1': 0.99513, 'iou': 0.99031, 'accuracy': 0.99269, 'contour_dice': 0.99513}, 1: {'f1': 0.97348, 'iou': 0.94833, 'accuracy': 0.98703, 'contour_dice': 0.97348}, 2: {'f1': 0.22896, 'iou': 0.12928, 'accuracy': 0.99176, 'contour_dice': 0.22896}}
-- Loss: 0.0929
+- Model Preparation Time: 0.001
+- Accuracy: 0.9683
+- F1: 0.9669
+- Iou: 0.9402
+- Contour Dice: 0.9519
+- Per Class Metrics: {0: {'f1': 0.98429, 'iou': 0.96907, 'accuracy': 0.97631, 'contour_dice': 0.98429}, 1: {'f1': 0.93449, 'iou': 0.87704, 'accuracy': 0.96872, 'contour_dice': 0.93449}, 2: {'f1': 0.42455, 'iou': 0.26948, 'accuracy': 0.99156, 'contour_dice': 0.42455}}
+- Loss: 0.5765
 
 ## Model description
 
@@ -55,22 +55,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Model Preparation Time |        | Dice   | Class Metrics                                                                                                                                                                                                                                          | Validation Loss |
 |:-------------:|:------:|:----:|:----------------------:|:------:|:------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------:|
-| 0.9835        | 0.1001 | 513  | 0.0011                 | 0.0355 | 0.3320 | {0: {'f1': 0.02025, 'iou': 0.01023, 'accuracy': 0.20562, 'contour_dice': 0.02025}, 1: {'f1': 0.20205, 'iou': 0.11238, 'accuracy': 0.13761, 'contour_dice': 0.20205}, 2: {'f1': 0.12505, 'iou': 0.06669, 'accuracy': 0.90513, 'contour_dice': 0.12505}} | 1.5839          |
-| 0.8946        | 0.2002 | 1026 | 0.0011                 | 0.6752 | 0.6622 | {0: {'f1': 0.83424, 'iou': 0.71563, 'accuracy': 0.77762, 'contour_dice': 0.83424}, 1: {'f1': 0.73093, 'iou': 0.57595, 'accuracy': 0.84974, 'contour_dice': 0.73093}, 2: {'f1': 0.02899, 'iou': 0.01471, 'accuracy': 0.90293, 'contour_dice': 0.02899}} | 0.9247          |
-| 0.8353        | 0.3002 | 1539 | 0.0011                 | 0.9172 | 0.9258 | {0: {'f1': 0.97708, 'iou': 0.95518, 'accuracy': 0.96497, 'contour_dice': 0.97708}, 1: {'f1': 0.90724, 'iou': 0.83024, 'accuracy': 0.95781, 'contour_dice': 0.90724}, 2: {'f1': 0.24247, 'iou': 0.13796, 'accuracy': 0.98702, 'contour_dice': 0.24247}} | 0.6193          |
-| 0.7437        | 0.4003 | 2052 | 0.0011                 | 0.9546 | 0.9688 | {0: {'f1': 0.98966, 'iou': 0.97952, 'accuracy': 0.98446, 'contour_dice': 0.98966}, 1: {'f1': 0.95343, 'iou': 0.911, 'accuracy': 0.97731, 'contour_dice': 0.95343}, 2: {'f1': 0.18273, 'iou': 0.10055, 'accuracy': 0.99138, 'contour_dice': 0.18273}}   | 0.5042          |
-| 0.7118        | 0.5004 | 2565 | 0.0011                 | 0.9715 | 0.9875 | {0: {'f1': 0.99578, 'iou': 0.99159, 'accuracy': 0.99368, 'contour_dice': 0.99578}, 1: {'f1': 0.97196, 'iou': 0.94546, 'accuracy': 0.98614, 'contour_dice': 0.97196}, 2: {'f1': 0.08536, 'iou': 0.04458, 'accuracy': 0.99092, 'contour_dice': 0.08536}} | 0.3568          |
-| 0.6965        | 0.6005 | 3078 | 0.0011                 | 0.9697 | 0.9821 | {0: {'f1': 0.99405, 'iou': 0.98816, 'accuracy': 0.99106, 'contour_dice': 0.99405}, 1: {'f1': 0.9723, 'iou': 0.9461, 'accuracy': 0.98647, 'contour_dice': 0.9723}, 2: {'f1': 0.2052, 'iou': 0.11433, 'accuracy': 0.99134, 'contour_dice': 0.2052}}      | 0.2106          |
-| 0.6643        | 0.7005 | 3591 | 0.0011                 | 0.9678 | 0.9849 | {0: {'f1': 0.99492, 'iou': 0.9899, 'accuracy': 0.9924, 'contour_dice': 0.99492}, 1: {'f1': 0.96694, 'iou': 0.936, 'accuracy': 0.98371, 'contour_dice': 0.96694}, 2: {'f1': 0.06056, 'iou': 0.03123, 'accuracy': 0.9907, 'contour_dice': 0.06056}}      | 0.2953          |
-| 0.6215        | 0.8006 | 4104 | 0.0011                 | 0.9605 | 0.9766 | {0: {'f1': 0.99232, 'iou': 0.98476, 'accuracy': 0.98844, 'contour_dice': 0.99232}, 1: {'f1': 0.95932, 'iou': 0.92183, 'accuracy': 0.98028, 'contour_dice': 0.95932}, 2: {'f1': 0.05829, 'iou': 0.03002, 'accuracy': 0.99085, 'contour_dice': 0.05829}} | 0.2461          |
-| 0.6155        | 0.9007 | 4617 | 0.0011                 | 0.9731 | 0.9897 | {0: {'f1': 0.99653, 'iou': 0.99309, 'accuracy': 0.99481, 'contour_dice': 0.99653}, 1: {'f1': 0.9727, 'iou': 0.94686, 'accuracy': 0.98657, 'contour_dice': 0.9727}, 2: {'f1': 0.11412, 'iou': 0.06051, 'accuracy': 0.99092, 'contour_dice': 0.11412}}   | 0.1863          |
-| 0.6058        | 1.0008 | 5130 | 0.0011                 | 0.9670 | 0.9808 | {0: {'f1': 0.99366, 'iou': 0.9874, 'accuracy': 0.99047, 'contour_dice': 0.99366}, 1: {'f1': 0.96863, 'iou': 0.93917, 'accuracy': 0.98474, 'contour_dice': 0.96863}, 2: {'f1': 0.11362, 'iou': 0.06023, 'accuracy': 0.99107, 'contour_dice': 0.11362}}  | 0.2076          |
-| 0.5948        | 1.1009 | 5643 | 0.0011                 | 0.9747 | 0.9888 | {0: {'f1': 0.99624, 'iou': 0.9925, 'accuracy': 0.99436, 'contour_dice': 0.99624}, 1: {'f1': 0.97498, 'iou': 0.95118, 'accuracy': 0.98772, 'contour_dice': 0.97498}, 2: {'f1': 0.28546, 'iou': 0.16649, 'accuracy': 0.99209, 'contour_dice': 0.28546}}  | 0.1954          |
-| 0.5824        | 1.2009 | 6156 | 0.0011                 | 0.9686 | 0.9859 | {0: {'f1': 0.9952, 'iou': 0.99045, 'accuracy': 0.99283, 'contour_dice': 0.9952}, 1: {'f1': 0.96787, 'iou': 0.93774, 'accuracy': 0.98404, 'contour_dice': 0.96787}, 2: {'f1': 0.05271, 'iou': 0.02707, 'accuracy': 0.99085, 'contour_dice': 0.05271}}   | 0.1422          |
-| 0.5849        | 1.3010 | 6669 | 0.0011                 | 0.9720 | 0.9854 | {0: {'f1': 0.99513, 'iou': 0.99031, 'accuracy': 0.99269, 'contour_dice': 0.99513}, 1: {'f1': 0.97348, 'iou': 0.94833, 'accuracy': 0.98703, 'contour_dice': 0.97348}, 2: {'f1': 0.22896, 'iou': 0.12928, 'accuracy': 0.99176, 'contour_dice': 0.22896}} | 0.0929          |
-| 0.5519        | 1.4011 | 7182 | 0.0011                 | 0.9671 | 0.9824 | {0: {'f1': 0.99417, 'iou': 0.9884, 'accuracy': 0.99124, 'contour_dice': 0.99417}, 1: {'f1': 0.96683, 'iou': 0.9358, 'accuracy': 0.98383, 'contour_dice': 0.96683}, 2: {'f1': 0.15623, 'iou': 0.08473, 'accuracy': 0.99138, 'contour_dice': 0.15623}}   | 0.1988          |
-| 0.5774        | 1.5012 | 7695 | 0.0011                 | 0.9677 | 0.9821 | {0: {'f1': 0.99407, 'iou': 0.98822, 'accuracy': 0.99109, 'contour_dice': 0.99407}, 1: {'f1': 0.96732, 'iou': 0.9367, 'accuracy': 0.9841, 'contour_dice': 0.96732}, 2: {'f1': 0.23996, 'iou': 0.13634, 'accuracy': 0.99184, 'contour_dice': 0.23996}}   | 0.1125          |
-| 0.5935        | 1.6012 | 8208 | 0.0011                 | 0.9721 | 0.9856 | {0: {'f1': 0.99523, 'iou': 0.9905, 'accuracy': 0.99284, 'contour_dice': 0.99523}, 1: {'f1': 0.97314, 'iou': 0.94768, 'accuracy': 0.98689, 'contour_dice': 0.97314}, 2: {'f1': 0.24074, 'iou': 0.13684, 'accuracy': 0.99185, 'contour_dice': 0.24074}}  | 0.1502          |
+| 1.0671        | 0.1001 | 513  | 0.001                  | 0.0174 | 0.3399 | {0: {'f1': 0.01146, 'iou': 0.00576, 'accuracy': 0.20842, 'contour_dice': 0.01146}, 1: {'f1': 0.10075, 'iou': 0.05305, 'accuracy': 0.14053, 'contour_dice': 0.10075}, 2: {'f1': 0.05262, 'iou': 0.02702, 'accuracy': 0.76933, 'contour_dice': 0.05262}} | 1.1976          |
+| 0.9789        | 0.2002 | 1026 | 0.001                  | 0.1266 | 0.4253 | {0: {'f1': 0.17912, 'iou': 0.09837, 'accuracy': 0.32393, 'contour_dice': 0.17912}, 1: {'f1': 0.35672, 'iou': 0.21708, 'accuracy': 0.29378, 'contour_dice': 0.35672}, 2: {'f1': 0.08294, 'iou': 0.04326, 'accuracy': 0.92794, 'contour_dice': 0.08294}} | 1.0129          |
+| 0.9142        | 0.3002 | 1539 | 0.001                  | 0.0798 | 0.3406 | {0: {'f1': 0.09007, 'iou': 0.04716, 'accuracy': 0.23534, 'contour_dice': 0.09007}, 1: {'f1': 0.30281, 'iou': 0.17842, 'accuracy': 0.21412, 'contour_dice': 0.30281}, 2: {'f1': 0.23584, 'iou': 0.13368, 'accuracy': 0.97521, 'contour_dice': 0.23584}} | 1.0183          |
+| 0.8372        | 0.4003 | 2052 | 0.001                  | 0.1395 | 0.3728 | {0: {'f1': 0.20698, 'iou': 0.11544, 'accuracy': 0.29956, 'contour_dice': 0.20698}, 1: {'f1': 0.35121, 'iou': 0.21301, 'accuracy': 0.28783, 'contour_dice': 0.35121}, 2: {'f1': 0.27184, 'iou': 0.1573, 'accuracy': 0.98612, 'contour_dice': 0.27184}}  | 0.9982          |
+| 0.7944        | 0.5004 | 2565 | 0.001                  | 0.7788 | 0.7999 | {0: {'f1': 0.90985, 'iou': 0.83461, 'accuracy': 0.87569, 'contour_dice': 0.90985}, 1: {'f1': 0.77275, 'iou': 0.62966, 'accuracy': 0.86359, 'contour_dice': 0.77275}, 2: {'f1': 0.31621, 'iou': 0.1878, 'accuracy': 0.98574, 'contour_dice': 0.31621}}  | 0.7430          |
+| 0.7582        | 0.6005 | 3078 | 0.001                  | 0.9402 | 0.9519 | {0: {'f1': 0.98429, 'iou': 0.96907, 'accuracy': 0.97631, 'contour_dice': 0.98429}, 1: {'f1': 0.93449, 'iou': 0.87704, 'accuracy': 0.96872, 'contour_dice': 0.93449}, 2: {'f1': 0.42455, 'iou': 0.26948, 'accuracy': 0.99156, 'contour_dice': 0.42455}} | 0.5765          |
+| 0.7361        | 0.7005 | 3591 | 0.001                  | 0.9085 | 0.9187 | {0: {'f1': 0.97374, 'iou': 0.94882, 'accuracy': 0.9603, 'contour_dice': 0.97374}, 1: {'f1': 0.89466, 'iou': 0.8094, 'accuracy': 0.9505, 'contour_dice': 0.89466}, 2: {'f1': 0.41467, 'iou': 0.26156, 'accuracy': 0.98929, 'contour_dice': 0.41467}}    | 0.6767          |
+| 0.6988        | 0.8006 | 4104 | 0.001                  | 0.1675 | 0.4246 | {0: {'f1': 0.24253, 'iou': 0.138, 'accuracy': 0.34598, 'contour_dice': 0.24253}, 1: {'f1': 0.40891, 'iou': 0.257, 'accuracy': 0.3392, 'contour_dice': 0.40891}, 2: {'f1': 0.34091, 'iou': 0.20548, 'accuracy': 0.98772, 'contour_dice': 0.34091}}      | 0.8428          |
+| 0.6579        | 0.9007 | 4617 | 0.001                  | 0.9375 | 0.9517 | {0: {'f1': 0.98326, 'iou': 0.96707, 'accuracy': 0.97513, 'contour_dice': 0.98326}, 1: {'f1': 0.93342, 'iou': 0.87515, 'accuracy': 0.96663, 'contour_dice': 0.93342}, 2: {'f1': 0.33019, 'iou': 0.19774, 'accuracy': 0.99099, 'contour_dice': 0.33019}} | 0.6605          |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:031d029f6f060a54e72c7a9853b5f213262d3b94c74c9da2cfab06c62123165f
+oid sha256:d551b568632b79078beabe6e6eb95c9924c6e971afbe0bc9d893c270505643d8
 size 2188724

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6c52ca8ff9bc554d465ab15a7c2d25820ed2c141ee2d0791f808040858f96985
+oid sha256:17e961eaf3a7355b900c971ef45eb6e8f4358aa83a2a12f9bb9fda92de959799
 size 5240