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  model-index:
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  - name: IKT_classifier_mitigation_best
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  results: []
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  # IKT_classifier_mitigation_best
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- 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.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6517
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  - Precision Micro: 0.3667
 
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  model-index:
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  - name: IKT_classifier_mitigation_best
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  results: []
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+ widget:
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+ - text: "Existing Gas Turbine power plant (570 MW)  Installation of prepaid meter  Bring down total T&D loss to a single digit by 2030 Transport  Improvement of road traffic congestion improvement in fuel efficiency)  Widening of roads (2 to 4 lanes) and improving road quality  Construct NMT and bicycle lanes  Electronic Road Pricing (ERP) or congestion charging  Reduction of private cars and encourage electric and hybrid vehicles  Development of Urban Transport Master Plans (UTMP) to improve transport systems in line with the Urban Plan/ City Plan for all major cities and urban area  Introducing Intelligent Transport System (ITS) based public transport management system to ensure better performance, enhance reliability, safety and service  Establish charging station network and electric buses in major cities  Modal shift from road to rail (25% modal shift of passenger-km) through different Transport projects such as BRT, MRT in major cities, Multi-modal hub creation, new bridges etc."
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+ example_title: ['Active mobility', 'Public transport improvement']
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+ - text: "Energy efficiency improvement measures include market transformation to energy efficient lighting that showed significant drop in electricity consumption that reached 40% in some buildings as well as improved energy efficiency in industrial sector through energy management systems and simple energy optimization measures. • Low Carbon Transport: The further expansion in the Greater Cairo underground metro network included the operation of stage 4 of length 11.5 km (Phase I: 2019, Phase II: 2020) of the third Cairo metro line as a progress towards achieving the modal shift to low carbon mass transit.14 The third line is the first metro to link east and west Cairo and is expected to serve 2 million passenger trips per day.15 The concept of high quality service buses has been introduced to Egypt targeting car owners to use the newly public transportation system that is integrated with the existing mass transit systems."
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+ example_title: ['Public transport improvement']
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+ - text: "Potential Actions Unconditional Contribution The targeted GHG emission reduction for unconditional contributions will be implemented through a set of mitigation actions. The potential mitigations actions are elaborated in Table 4. Table 4: Possible Mitigation Actions to deliver the Unconditional Contribution Sector Description Actions by 2030 Energy Power  Implementation of renewable energy projects  Enhanced efficiency of existing power plants  Use of improved technology for power generation Transport  Improvement of fuel efficiency for transport sub- sector  Increase use of less emission- based transport system and improve Inland Water Transport System Power  Implementation of renewable energy projects of 911.8 MW  Grid-connected Solar-581 MW, Wind-149 MW, MW, Solar Mini-grid-56.8 MW  Installation of new Combined Cycle Gas based power plant (3208 MW)  Efficiency improvement of Existing Gas Turbine power plant (570 MW)  Installation of prepaid meter Transport  Improvement of road traffic congestion improvement in"
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+ example_title: ['Vehicle improvements', 'Improve infrastructure']
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # IKT_classifier_mitigation_best
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+ 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.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6517
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  - Precision Micro: 0.3667