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README.md

@@ -15,15 +15,15 @@ widget:
 
 | Metric                   | Value                           |
 |--------------------------|---------------------------------|
-| Duration (in seconds)    | 29510.494063854218  |
-| Emissions (Co2eq in kg)  | 0.0178572448003947 |
+| Duration (in seconds)    | 37993.74807047844  |
+| Emissions (Co2eq in kg)  | 0.0229906147552034 |
 | CPU power (W)            | 42.5  |
 | GPU power (W)            | [No GPU]  |
 | RAM power (W)            | 3.75  |
-| CPU energy (kWh)         | 0.3483869561615912  |
+| CPU energy (kWh)         | 0.4485365634348655  |
 | GPU energy (kWh)         | [No GPU]  |
-| RAM energy (kWh)         | 0.0307397035780052  |
-| Consumed energy (kWh)    | 0.3791266597395957  |
+| RAM energy (kWh)         | 0.0395765287543337  |
+| Consumed energy (kWh)    | 0.4881130921891984  |
 | Country name             | Switzerland  |
 | Cloud provider           | nan  |
 | Cloud region             | nan  |
@@ -36,8 +36,8 @@ widget:
 
 | Metric                   | Value                           |
 |--------------------------|---------------------------------|
-| CPU energy (kWh)         | 0.05680770107291936  |
-| Emissions (Co2eq in kg)  | 0.011558276841676233 |
+| CPU energy (kWh)         | 0.07313796503567101  |
+| Emissions (Co2eq in kg)  | 0.014880884660937389 |
 
 ## Note
 
@@ -50,7 +50,7 @@ widget:
 | checkpoint               | albert-base-v2  |
 | model_name               | BERTrand_base_x2 |
 | sequence_length          | 400  |
-| num_epoch                | 3  |
+| num_epoch                | 6  |
 | learning_rate            | 9e-06  |
 | batch_size               | 16  |
 | weight_decay             | 0.0  |
@@ -58,7 +58,7 @@ widget:
 | drop_out_prob            | 0.1 |
 | packing_length           | 100 |
 | train_test_split         | 0.2 |
-| num_steps                | 18330 |
+| num_steps                | 36660 |
 
 ## Training and Testing steps
 
@@ -70,7 +70,10 @@ widget:
  
 Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP
 ---|---|---|---|---|---|---|---
-| 0 | 0.000000 | 0.685451 | 0.000000 | 752.000000 | 10.000000 | 766.000000 | 0.000000 |
-| 1 | 0.296231 | 0.215547 | 0.944671 | 645.000000 | 117.000000 | 25.000000 | 741.000000 |
-| 2 | 0.176286 | 0.201471 | 0.945044 | 668.000000 | 94.000000 | 30.000000 | 736.000000 |
-| 3 | 0.120724 | 0.218803 | 0.891585 | 711.000000 | 51.000000 | 90.000000 | 676.000000 |
+| 0 | 0.000000 | 0.762512 | 0.001627 | 753.000000 | 9.000000 | 765.000000 | 1.000000 |
+| 1 | 0.285383 | 0.236045 | 0.945052 | 638.000000 | 124.000000 | 23.000000 | 743.000000 |
+| 2 | 0.171418 | 0.223179 | 0.937339 | 662.000000 | 100.000000 | 36.000000 | 730.000000 |
+| 3 | 0.113694 | 0.209987 | 0.938465 | 671.000000 | 91.000000 | 37.000000 | 729.000000 |
+| 4 | 0.064221 | 0.242213 | 0.933953 | 674.000000 | 88.000000 | 42.000000 | 724.000000 |
+| 5 | 0.041251 | 0.297383 | 0.924348 | 669.000000 | 93.000000 | 50.000000 | 716.000000 |
+| 6 | 0.029554 | 0.291359 | 0.926215 | 690.000000 | 72.000000 | 53.000000 | 713.000000 |