diff --git a/README.md b/README.md
index 3b358ad..e631234 100644
--- a/README.md
+++ b/README.md
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [vinvino02/glpn-nyu](https://huggingface.co/vinvino02/glpn-nyu) on the diode-subset dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8193
-- Rmse: 0.8077
+- Loss: 0.4359
+- Rmse: 0.4276
 
 ## Model description
 
@@ -36,29 +36,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- learning_rate: 2e-05
+- train_batch_size: 24
+- eval_batch_size: 24
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 10
+- mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Rmse   |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 1.0   | 10   | 0.9152          | nan    |
-| 0.8958        | 2.0   | 20   | 0.8413          | nan    |
-| 0.8958        | 3.0   | 30   | 0.7873          | 1.0697 |
-| 0.7472        | 4.0   | 40   | 0.7405          | 0.9340 |
-| 0.7472        | 5.0   | 50   | 0.7017          | 0.8441 |
-| 0.6999        | 6.0   | 60   | 0.6785          | 0.7959 |
-| 0.6999        | 7.0   | 70   | 0.6656          | 0.7672 |
-| 0.6917        | 8.0   | 80   | 0.6490          | 0.7413 |
-| 0.6917        | 9.0   | 90   | 0.6413          | 0.7212 |
-| 0.6527        | 10.0  | 100  | 0.6408          | 0.7146 |
+| No log        | 1.0   | 13   | 1.2498          | 0.9726 |
+| 0.8469        | 2.0   | 26   | 1.0661          | nan    |
+| 0.8469        | 3.0   | 39   | 0.9959          | 0.5287 |
+| 0.6946        | 4.0   | 52   | 0.8550          | 0.4084 |
+| 0.586         | 5.0   | 65   | 0.7679          | 0.3603 |
+| 0.586         | 6.0   | 78   | 0.6650          | 0.3119 |
+| 0.5195        | 7.0   | 91   | 0.6837          | 0.3370 |
+| 0.4737        | 8.0   | 104  | 0.6638          | 0.3366 |
+| 0.4737        | 9.0   | 117  | 0.6522          | 0.3250 |
+| 0.4663        | 10.0  | 130  | 0.6461          | 0.3153 |
 
 
 ### Framework versions