update model card README.md

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: sentence-transformers/all-mpnet-base-v2
 tags:
 - generated_from_trainer
 metrics:
@@ -7,17 +8,6 @@ metrics:
 model-index:
 - name: IKT_classifier_netzero_best
   results: []
-  
-widget:
-- text: >-
-    "We have put forth a long-term low- emissions development strategy (LEDS) that aspires to halve emissions from its peak to 33 MtCO2e by 2050, with a view to achieving net-zero emissions as soon as viable in the second half of the century. This will require serious and concerted efforts across our industry, economy and society"
-  example_title: NET-ZERO
-- text: >-
-    "Unconditional Contribution In the unconditional scenario, GHG emissions would be reduced by 27.56 Mt CO2e (6.73%) below BAU in 2030 in the respective sectors. 26.3 Mt CO2e (95.4%) of this emission reduction will be from the Energy sector while 0.64 (2.3%) and 0.6 (2.2%) Mt CO2e reduction will be from AFOLU (agriculture) and waste sector respectively. There will be no reduction in the IPPU sector. Conditional Contribution In the conditional scenario, GHG emissions would be reduced by 61.9 Mt CO2e (15.12%) below BAU in 2030 in the respective sectors."
-  example_title: TARGET_FREE
-- text: >-
-    "This land is buffered from the sea by the dyke and a network of drains and pumps will control the water levels in the polder. We have raised the minimum platform levels for new developments from 3m to 4m above the Singapore Height Datum (SHD) since 2011. Presently, critical infrastructure on existing coastal land, notably Changi Airport Terminal 5 and Tuas Port, will be constructed with platform levels at least 5m above SHD."
-  example_title: NEGATIVE
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -27,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.9526
-- Precision Macro: 0.7813
-- Precision Weighted: 0.8164
-- Recall Macro: 0.7734
-- Recall Weighted: 0.7812
-- F1-score: 0.7644
-- Accuracy: 0.7812
+- Loss: 0.4126
+- Precision Macro: 0.9246
+- Precision Weighted: 0.9248
+- Recall Macro: 0.9209
+- Recall Weighted: 0.9211
+- F1-score: 0.9219
+- Accuracy: 0.9211
 
 ## Model description
 
@@ -59,25 +49,22 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 400.0
-- num_epochs: 8
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
-| No log        | 1.0   | 114  | 0.8267          | 0.8056          | 0.8151             | 0.6601       | 0.6875          | 0.6418   | 0.6875   |
-| No log        | 2.0   | 228  | 0.4916          | 0.8095          | 0.8371             | 0.8290       | 0.8125          | 0.8113   | 0.8125   |
-| No log        | 3.0   | 342  | 0.4784          | 0.8535          | 0.8920             | 0.8682       | 0.875           | 0.8569   | 0.875    |
-| No log        | 4.0   | 456  | 0.8909          | 0.7813          | 0.8164             | 0.7734       | 0.7812          | 0.7644   | 0.7812   |
-| 0.6167        | 5.0   | 570  | 0.6673          | 0.8242          | 0.8650             | 0.8649       | 0.8125          | 0.8260   | 0.8125   |
-| 0.6167        | 6.0   | 684  | 0.7110          | 0.8413          | 0.8795             | 0.8845       | 0.8438          | 0.8505   | 0.8438   |
-| 0.6167        | 7.0   | 798  | 1.3731          | 0.7778          | 0.8281             | 0.7702       | 0.7188          | 0.7380   | 0.7188   |
-| 0.6167        | 8.0   | 912  | 0.9526          | 0.7813          | 0.8164             | 0.7734       | 0.7812          | 0.7644   | 0.7812   |
+| No log        | 1.0   | 113  | 0.7402          | 0.8808          | 0.8847             | 0.8697       | 0.8684          | 0.8694   | 0.8684   |
+| No log        | 2.0   | 226  | 0.8484          | 0.84            | 0.8358             | 0.6752       | 0.6842          | 0.6675   | 0.6842   |
+| No log        | 3.0   | 339  | 0.3188          | 0.9209          | 0.9229             | 0.9209       | 0.9211          | 0.9200   | 0.9211   |
+| No log        | 4.0   | 452  | 0.5524          | 0.8889          | 0.8925             | 0.8718       | 0.8684          | 0.8689   | 0.8684   |
+| 0.5553        | 5.0   | 565  | 0.4126          | 0.9246          | 0.9248             | 0.9209       | 0.9211          | 0.9219   | 0.9211   |
 
 
 ### Framework versions
 
-- Transformers 4.30.2
+- Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.13.1
 - Tokenizers 0.13.3