End of training

README.md

@@ -15,17 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [nvidia/mit-b4](https://huggingface.co/nvidia/mit-b4) on the None dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.1800
-- eval_mean_iou: 0.9263
-- eval_mean_accuracy: 0.9672
-- eval_overall_accuracy: 0.9672
-- eval_per_category_iou: [0.9263180856590626]
-- eval_per_category_accuracy: [0.9671769089820561]
-- eval_runtime: 733.0358
-- eval_samples_per_second: 1.247
-- eval_steps_per_second: 0.312
-- epoch: 3.0
-- step: 1371
+- Loss: 0.1675
+- Mean Iou: 0.7570
+- Mean Accuracy: 0.8341
+- Overall Accuracy: 0.9396
+- Per Category Iou: [0.9341045714153958, 0.5798374949488075]
+- Per Category Accuracy: [0.9728893841433082, 0.6952250066198535]
 
 ## Model description
 
@@ -52,6 +47,22 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 10
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                         | Per Category Accuracy                    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:----------------------------------------:|
+| 0.1426        | 1.0   | 457  | 0.1936          | 0.6822   | 0.7438        | 0.9242           | [0.9193425271297406, 0.4449612711247542] | [0.9811465495367065, 0.5065393570873438] |
+| 0.1066        | 2.0   | 914  | 0.1840          | 0.7247   | 0.8166        | 0.9281           | [0.921792369706966, 0.5275532773693746]  | [0.9632516253169541, 0.6698574354887572] |
+| 0.1902        | 3.0   | 1371 | 0.1825          | 0.7341   | 0.8195        | 0.9320           | [0.9260615811301273, 0.5422064806171729] | [0.9674973788201077, 0.6715653524785264] |
+| 0.0337        | 4.0   | 1828 | 0.1754          | 0.7271   | 0.7949        | 0.9338           | [0.9285138951582051, 0.5256281586371581] | [0.9775754623882825, 0.6121479072473499] |
+| 0.0282        | 5.0   | 2285 | 0.1959          | 0.7395   | 0.8653        | 0.9262           | [0.9184942871535651, 0.5605025991065423] | [0.9453582612880436, 0.7853124151415186] |
+| 0.2816        | 6.0   | 2742 | 0.1763          | 0.7331   | 0.8035        | 0.9347           | [0.9293865372531065, 0.5367951843584413] | [0.9761229104877399, 0.6308764449372819] |
+| 0.1378        | 7.0   | 3199 | 0.1707          | 0.7495   | 0.8309        | 0.9369           | [0.931185547791987, 0.5677946512496371]  | [0.9703251796700836, 0.691472671396249]  |
+| 0.1596        | 8.0   | 3656 | 0.1654          | 0.7511   | 0.8228        | 0.9390           | [0.9337197231959533, 0.5685273561265333] | [0.9757118594786471, 0.6698855265722331] |
+| 0.0751        | 9.0   | 4113 | 0.1658          | 0.7478   | 0.8151        | 0.9390           | [0.9338284931081033, 0.5617165036252598] | [0.9780982401336578, 0.6520209898525051] |
+| 0.0682        | 10.0  | 4570 | 0.1675          | 0.7570   | 0.8341        | 0.9396           | [0.9341045714153958, 0.5798374949488075] | [0.9728893841433082, 0.6952250066198535] |
+
+
 ### Framework versions
 
 - Transformers 4.33.1