End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: other
-base_model: nvidia/mit-b4
+base_model: nvidia/mit-b3
 tags:
 - generated_from_trainer
 model-index:
@@ -13,19 +13,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # segformer_cracks
 
-This model is a fine-tuned version of [nvidia/mit-b4](https://huggingface.co/nvidia/mit-b4) on the None dataset.
+This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the None dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 1.3172
-- eval_mean_iou: 0.4811
-- eval_mean_accuracy: 0.5
-- eval_overall_accuracy: 0.9623
-- eval_per_category_iou: [0.962250074678964, 0.0]
-- eval_per_category_accuracy: [1.0, 0.0]
-- eval_runtime: 3654.1653
-- eval_samples_per_second: 0.75
-- eval_steps_per_second: 0.187
-- epoch: 3.0
-- step: 4110
+- Loss: 0.0499
+- Mean Iou: 0.7718
+- Mean Accuracy: 0.8317
+- Overall Accuracy: 0.9798
+- Per Category Iou: [0.9792869895386617, 0.564265846038068]
+- Per Category Accuracy: [0.9923313345080351, 0.671108360646227]
 
 ## Model description
 
@@ -44,13 +39,26 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 6e-05
+- learning_rate: 3e-05
 - train_batch_size: 8
-- eval_batch_size: 4
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                         | Per Category Accuracy                    |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:----------------------------------------:|
+| 0.0686        | 1.0   | 1541  | 0.0557          | 0.7541   | 0.8082        | 0.9785           | [0.9779708221514636, 0.5303006858963294] | [0.9928845967047768, 0.6234677160845897] |
+| 0.049         | 2.0   | 3082  | 0.0527          | 0.7633   | 0.8239        | 0.9790           | [0.9784073819168878, 0.5481400031368636] | [0.9920481107810992, 0.6557623260692017] |
+| 0.0468        | 3.0   | 4623  | 0.0547          | 0.7526   | 0.7996        | 0.9788           | [0.9783360187606548, 0.5269084757862701] | [0.993975994702418, 0.6052805015161615]  |
+| 0.0456        | 4.0   | 6164  | 0.0509          | 0.7677   | 0.8276        | 0.9794           | [0.9788937969015667, 0.556522438909845]  | [0.9922581622702671, 0.6629042271896711] |
+| 0.044         | 5.0   | 7705  | 0.0505          | 0.7678   | 0.8265        | 0.9795           | [0.9789809420595871, 0.5566804258721124] | [0.9924358981457169, 0.6606494246283242] |
+| 0.0436        | 6.0   | 9246  | 0.0502          | 0.7696   | 0.8265        | 0.9798           | [0.9792607857315766, 0.5598563478221208] | [0.9927329763880554, 0.6603118480646505] |
+| 0.0431        | 7.0   | 10787 | 0.0499          | 0.7718   | 0.8317        | 0.9798           | [0.9792869895386617, 0.564265846038068]  | [0.9923313345080351, 0.671108360646227]  |
+
 
 ### Framework versions