update model card README.md

README.md

@@ -8,14 +8,6 @@ metrics:
 model-index:
 - name: IKT_classifier_conditional_best
   results: []
-
-widget:
-- text: "Brick Kilns. Enforcement and Improved technology use. Residential and Commercial. Enhanced use of energy- efficient appliances in household and commercial buildings. F-Gases. Implement Montreal Protocol targets. Industry. Achieve 10% Energy efficiency in the Industry sub-sector through measures according to the Energy Efficiency and Conservation Master Plan (EECMP). Agriculture. Implementation of 5925 Nos. solar irrigation pumps (generating 176.38MW) for agriculture. Brick Kilns. 14% emission reduction through Banning Fixed Chimney kiln (FCK), encourage advanced technology and non-fired brick use. Residential and Commercial."
-  example_title: UNCONDITIONAL
-- text: "Achieve 20% Energy efficiency in the Industry sub-sector through measures according to the Energy Efficiency and Conservation Master Plan (EECMP). Promote green Industry. Promote carbon financing. Agriculture. Enhanced use of solar energy in Agriculture. Agriculture. Implementation of 4102 Nos. solar irrigation pumps (generating 164 MW) for agriculture. Brick Kilns. Enforcement and Improved technology use. Brick Kilns. 47% emission reduction through Banning Fixed Chimney kiln (FCK), encourage advanced technology and non-fired brick use. Residential and Commercial."
-  example_title: CONDITIONAL
-- text: "The GHG emission reductions from Cairo metro network includes the rehabilitation of existing lines 1, 2, and 3. • The development of Alexandria Metro (Abu Qir – Alexandria railway line) and rehabilitation of the Raml tram line."
-  example_title: CONDITIONAL
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -23,15 +15,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 # IKT_classifier_conditional_best
 
-This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the [GIZ/policy_qa_v0_1](https://huggingface.co/datasets/GIZ/policy_qa_v0_1) dataset.
+This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9766
-- Precision Macro: 0.8010
-- Precision Weighted: 0.8078
-- Recall Macro: 0.7928
-- Recall Weighted: 0.8093
-- F1-score: 0.7963
-- Accuracy: 0.8093
+- Loss: 0.5371
+- Precision Macro: 0.8714
+- Precision Weighted: 0.8713
+- Recall Macro: 0.8711
+- Recall Weighted: 0.8712
+- F1-score: 0.8712
+- Accuracy: 0.8712
 
 ## Model description
 
@@ -63,11 +55,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
-| 0.6562        | 1.0   | 696  | 0.5617          | 0.7283          | 0.7423             | 0.7283       | 0.7423          | 0.7283   | 0.7423   |
-| 0.6091        | 2.0   | 1392 | 0.6492          | 0.7345          | 0.7443             | 0.7251       | 0.7474          | 0.7287   | 0.7474   |
-| 0.3892        | 3.0   | 2088 | 0.7730          | 0.7848          | 0.7872             | 0.7612       | 0.7887          | 0.7687   | 0.7887   |
-| 0.2509        | 4.0   | 2784 | 0.9735          | 0.7778          | 0.7937             | 0.7858       | 0.7887          | 0.7807   | 0.7887   |
-| 0.1648        | 5.0   | 3480 | 0.9766          | 0.8010          | 0.8078             | 0.7928       | 0.8093          | 0.7963   | 0.8093   |
+| 0.6658        | 1.0   | 698  | 0.7196          | 0.7391          | 0.7381             | 0.7102       | 0.7124          | 0.7028   | 0.7124   |
+| 0.6301        | 2.0   | 1396 | 0.4965          | 0.8073          | 0.8075             | 0.8071       | 0.8069          | 0.8069   | 0.8069   |
+| 0.5252        | 3.0   | 2094 | 0.5307          | 0.8300          | 0.8297             | 0.8279       | 0.8283          | 0.8279   | 0.8283   |
+| 0.3513        | 4.0   | 2792 | 0.5261          | 0.8626          | 0.8627             | 0.8626       | 0.8627          | 0.8626   | 0.8627   |
+| 0.2979        | 5.0   | 3490 | 0.5371          | 0.8714          | 0.8713             | 0.8711       | 0.8712          | 0.8712   | 0.8712   |
 
 
 ### Framework versions