Update README.md

README.md

@@ -9,13 +9,13 @@ model-index:
 datasets:
 - GIZ/policy_classification
 co2_eq_emissions:
-  emissions: 23.3572576873636
+  emissions: 37.5331346075112
   source: codecarbon
   training_type: fine-tuning
   on_cloud: true
   cpu_model: Intel(R) Xeon(R) CPU @ 2.00GHz
   ram_total_size: 12.6747894287109
-  hours_used: 0.529
+  hours_used: 0.659
   hardware_used: 1 x Tesla T4
 ---
 
@@ -48,21 +48,18 @@ More information needed
 
 ## Training and evaluation data
 
-- Training Dataset: 10031
+- Training Dataset: 12538
 | Class | Positive Count of Class|
 |:-------------|:--------|
-| Action | 5416 |
-| Plans | 2140 |
-| Policy | 1396|
-| Target | 2911 |
+| AdaptationLabel | 5439 |
+| MitigationLabel | 6659 |
 
-- Validation Dataset: 932
+
+- Validation Dataset: 1190
 | Class | Positive Count of Class|
 |:-------------|:--------|
-| Action | 513 |
-| Plans | 198 |
-| Policy | 122 |
-| Target | 256 |
+| AdaptationLabel | 533 |
+| MitigationLabel | 604 |
 
 ## Training procedure
 
@@ -90,10 +87,20 @@ The following hyperparameters were used during training:
 
 |label          | precision |recall |f1-score| support|
 |:-------------:|:---------:|:-----:|:------:|:------:|
-|Action	|0.828   	|0.807  |0.817   |	513.0  |
-|Plans	        |0.560	    |0.707  |0.625   |	198.0  |
-|Policy	|0.727      |0.786  |0.756   |	122.0  |
-|Target	    |0.741     |0.886  |0.808  |	256.0  |
+|AdaptationLabel	|0.909   	|0.908  |0.909   |	533.0  |
+|MitigationLabel	|0.891	    |0.925  |0.908   |	604.0  |
+
+
+### Environmental Impact
+Carbon emissions were measured using [CodeCarbon](https://github.com/mlco2/codecarbon).
+- **Carbon Emitted**: 0.0375 kg of CO2
+- **Hours Used**: 0.659 hours
+
+### Training Hardware
+- **On Cloud**: yes
+- **GPU Model**: 1 x Tesla T4
+- **CPU Model**: Intel(R) Xeon(R) CPU @ 2.00GHz
+- **RAM Size**: 12.67 GB
 
 ### Framework versions