|
|
--- |
|
|
license: cc-by-4.0 |
|
|
base_model: deepset/roberta-base-squad2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: roberta-finetuned-qa-policy_2 |
|
|
results: [] |
|
|
|
|
|
widget: |
|
|
- text: What are the Adaptation action/priority for the LULUCF/Forestry Sector? |
|
|
context: >- |
|
|
Construction of fire belts to reduce the burning of forest land. Introduce drought, |
|
|
temperature and flood resistant crops. Improve infrastructure and water management |
|
|
(irrigation and water harvesting). Develop and regulate effective animal grassing system. |
|
|
Develop structures for conflict resolution in respect of Land use. |
|
|
Integrated management of crops and Livestock management. Strategy. Goal: |
|
|
Ensure integrated and sustainable crop and Livestock production. Introduce pest and disease resilient crops. |
|
|
25,000,000. Control free range animal grazing. Embank on effective agricultural research. |
|
|
- text: What adaptation/mitigation/net-zero targets/objectives are provided for the Transport Sector ? |
|
|
context: >- |
|
|
This updated NDC includes ambitious mitigation target for Energy |
|
|
(electricity generation and transport), Waste and Agriculture |
|
|
Forestry and Other Land Use (AFOLU) sector. For the energy sector, |
|
|
the two main targets are - 86% renewable energy generation from local |
|
|
resources in the electricity sector by 2030 and 100% of new vehicle |
|
|
sales to be electric vehicles by 2030. While the transport sector |
|
|
target is set to be achieved by 2040, |
|
|
continuous actions will be taken starting 2025. |
|
|
- text: What adaptation/mitigation/net-zero targets/objectives are provided for the Energy Sector ? |
|
|
context: >- |
|
|
The electricity and transport sectors are the main usage sectors |
|
|
of fossil fuels in the country and the electricity demand is expected |
|
|
to increase in the medium term. Accordingly the Government has defined the |
|
|
policy framework for a low carbon development plan through the |
|
|
National Energy Policy, that sets a target to achieve a minimum of 30% renewables |
|
|
in the energy mix by 2030 and will allow for a |
|
|
10% Residential Energy Self Generation Programme within the year. |
|
|
- text: How freight efficiency improvements correlates with mitigation targets? |
|
|
context: >- |
|
|
That requires substantial investment in combined-cycle gas turbine (CCGT) |
|
|
power plants and LNG import capacity. In the transportation sector, |
|
|
emissions savings can be achieved by developing rail for passengers and freight, |
|
|
urban public transportation, and the electrification of the passenger and, |
|
|
light-duty vehicle fleet. Figure 10: GHG emissions projections for the |
|
|
energy sector in the LTS4CN scenario The LTS4CN scenario suggests five |
|
|
mitigation actions for the IPPU sector that could avoid a |
|
|
total of 9.1 MtCO2e of emissions compared to 10.7 MtCO2e under BAU. |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# roberta-finetuned-qa-policy_2 |
|
|
|
|
|
This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset. |
|
|
|
|
|
## Model description |
|
|
|
|
|
More information needed |
|
|
|
|
|
## Intended uses & limitations |
|
|
|
|
|
More information needed |
|
|
|
|
|
## Training and evaluation data |
|
|
|
|
|
More information needed |
|
|
|
|
|
## Training procedure |
|
|
|
|
|
### Training hyperparameters |
|
|
|
|
|
The following hyperparameters were used during training: |
|
|
- learning_rate: 2e-05 |
|
|
- train_batch_size: 8 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 32 |
|
|
- total_train_batch_size: 256 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 7 |
|
|
|
|
|
### Training results |
|
|
|
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.33.2 |
|
|
- Pytorch 2.0.1+cu118 |
|
|
- Datasets 2.14.5 |
|
|
- Tokenizers 0.13.3 |
|
|
|