End of training

README.md

@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0253
+- Loss: 5.4000
 
 ## Model description
 
@@ -34,7 +34,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.0005
 - train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
@@ -47,16 +47,31 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 2.5385        | 0.1   | 250  | 1.9164          |
-| 1.952         | 0.2   | 500  | 1.6952          |
-| 1.7037        | 0.3   | 750  | 1.6839          |
-| 1.5698        | 0.4   | 1000 | 1.4518          |
-| 1.4471        | 0.5   | 1250 | 1.4302          |
-| 1.3161        | 0.6   | 1500 | 1.2422          |
-| 1.2208        | 0.7   | 1750 | 1.1559          |
-| 1.1466        | 0.8   | 2000 | 1.0832          |
-| 1.1077        | 0.9   | 2250 | 1.0370          |
-| 1.0793        | 1.0   | 2500 | 1.0253          |
+| 3.4552        | 0.04  | 100  | 5.8812          |
+| 3.0646        | 0.08  | 200  | 6.1299          |
+| 2.8724        | 0.12  | 300  | 5.4912          |
+| 2.7418        | 0.16  | 400  | 6.3882          |
+| 2.6577        | 0.2   | 500  | 5.5691          |
+| 2.5283        | 0.24  | 600  | 5.7357          |
+| 2.4574        | 0.28  | 700  | 5.6403          |
+| 2.3614        | 0.32  | 800  | 5.4325          |
+| 2.342         | 0.36  | 900  | 6.4478          |
+| 2.3154        | 0.4   | 1000 | 5.8527          |
+| 2.3305        | 0.44  | 1100 | 5.8006          |
+| 2.2296        | 0.48  | 1200 | 5.5432          |
+| 2.2821        | 0.52  | 1300 | 5.3882          |
+| 2.2623        | 0.56  | 1400 | 5.3867          |
+| 2.1653        | 0.6   | 1500 | 5.9831          |
+| 2.1729        | 0.64  | 1600 | 5.5752          |
+| 2.1155        | 0.68  | 1700 | 5.4664          |
+| 2.094         | 0.72  | 1800 | 5.5329          |
+| 2.0948        | 0.76  | 1900 | 5.4304          |
+| 1.9956        | 0.8   | 2000 | 5.9376          |
+| 2.0062        | 0.84  | 2100 | 5.7035          |
+| 2.0472        | 0.88  | 2200 | 5.4439          |
+| 2.0699        | 0.92  | 2300 | 5.3537          |
+| 1.9993        | 0.96  | 2400 | 5.3219          |
+| 1.9494        | 1.0   | 2500 | 5.4000          |
 
 
 ### Framework versions