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Training in progress, step 1000
Browse files- README.md +83 -0
- config.json +174 -174
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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---
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library_name: transformers
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base_model: microsoft/deberta-v3-small
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: doc-topic-model_eval-00_train-03
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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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should probably proofread and complete it, then remove this comment. -->
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# doc-topic-model_eval-00_train-03
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0375
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- Accuracy: 0.9878
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- F1: 0.6375
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- Precision: 0.7079
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- Recall: 0.5798
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 256
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 100
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.0923 | 0.4931 | 1000 | 0.0865 | 0.9815 | 0.0 | 0.0 | 0.0 |
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| 0.0734 | 0.9862 | 2000 | 0.0668 | 0.9815 | 0.0 | 0.0 | 0.0 |
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| 0.0606 | 1.4793 | 3000 | 0.0552 | 0.9824 | 0.1265 | 0.7701 | 0.0689 |
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| 0.0532 | 1.9724 | 4000 | 0.0491 | 0.9841 | 0.2944 | 0.8178 | 0.1795 |
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| 0.0466 | 2.4655 | 5000 | 0.0467 | 0.9851 | 0.4323 | 0.7342 | 0.3063 |
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| 0.0433 | 2.9586 | 6000 | 0.0428 | 0.9859 | 0.4847 | 0.7565 | 0.3566 |
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| 0.0391 | 3.4517 | 7000 | 0.0408 | 0.9866 | 0.5389 | 0.7450 | 0.4221 |
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| 0.0378 | 3.9448 | 8000 | 0.0395 | 0.9867 | 0.5527 | 0.7365 | 0.4423 |
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| 0.0338 | 4.4379 | 9000 | 0.0387 | 0.9870 | 0.5844 | 0.7160 | 0.4936 |
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| 0.0333 | 4.9310 | 10000 | 0.0380 | 0.9871 | 0.5953 | 0.7094 | 0.5128 |
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| 0.0301 | 5.4241 | 11000 | 0.0371 | 0.9876 | 0.6042 | 0.7368 | 0.5120 |
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| 0.0292 | 5.9172 | 12000 | 0.0367 | 0.9877 | 0.6120 | 0.7381 | 0.5227 |
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| 0.0266 | 6.4103 | 13000 | 0.0369 | 0.9879 | 0.6132 | 0.7535 | 0.5170 |
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| 0.0257 | 6.9034 | 14000 | 0.0371 | 0.9877 | 0.6187 | 0.7257 | 0.5392 |
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| 0.0229 | 7.3964 | 15000 | 0.0371 | 0.9880 | 0.6330 | 0.7279 | 0.5600 |
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| 0.0238 | 7.8895 | 16000 | 0.0372 | 0.9879 | 0.6306 | 0.7250 | 0.5579 |
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| 0.0198 | 8.3826 | 17000 | 0.0375 | 0.9878 | 0.6375 | 0.7079 | 0.5798 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Agribusiness and Value Chains":
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"Agriculture and Food":
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"Biodiversity":
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"COVID-19 Hub":
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"Climate Change":
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"Climate-Smart Agriculture":
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"Community-Driven Development":
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"Competition Policy":
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"Competitiveness":
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"Credit Infrastructure":
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"Debt":
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"Debt Relief":
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"Digital Development":
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"Disability Inclusion":
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"Disaster Risk Management":
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"Early Childhood Development":
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"Education":
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"Education and Technology":
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"Energy":
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"Environment":
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"Extractive Industries":
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"Financial Inclusion":
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"Financial Integrity":
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"Financial Sector":
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"Financial Stability":
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"Food Security Update":
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"Food System Jobs":
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"Forests and Landscapes":
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"Fragility, Conflict, and Violence":
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"Gas Flaring Reduction":
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"Gender":
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"Girls' Education":
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"Global Financing Facility for Women, Children and Adolescents":
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"Global Value Chains":
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"Governance":
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"Health":
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"Inequality and Shared Prosperity":
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"Infectious diseases and Vaccines":
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"Infrastructure":
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"Long-Term Finance":
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"Natural Capital":
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"Oceans, Fisheries, and Coastal Economies":
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},
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "Indigenous Peoples",
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"1": "Investment Climate",
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"2": "Marine Plastic Pollution",
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"3": "Poverty",
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"4": "Water",
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"5": "Measuring Poverty",
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"6": "Energy",
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"7": "Sustainable Communities",
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"8": "Disability Inclusion",
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"9": "Macroeconomics",
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"10": "Early Childhood Development",
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"11": "Mining Investment and Governance Review",
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"12": "Infrastructure",
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"13": "Community-Driven Development",
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"14": "Land",
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"15": "Innovation and Entrepreneurship",
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"16": "Competitiveness",
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"17": "Biodiversity",
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"18": "Debt",
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"19": "Higher Education",
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"20": "Livestock and Sustainability",
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"21": "Universal Health Coverage",
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"22": "Nutrition",
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"23": "Education and Technology",
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"24": "Small and Medium Enterprises Finance",
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"25": "Climate-Smart Agriculture",
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"26": "Food Security Update",
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"27": "Inclusive Cities",
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"28": "Jobs & Development",
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"29": "Migration",
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"30": "Infectious diseases and Vaccines",
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"31": "Social Protection",
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"32": "Skills Development",
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"33": "Governance",
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"34": "Pollution",
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"35": "Inequality and Shared Prosperity",
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"36": "Oceans, Fisheries, and Coastal Economies",
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"37": "Global Value Chains",
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"38": "Pensions",
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"39": "Food System Jobs",
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"40": "Debt Relief",
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"41": "Sexual Orientation and Gender Identity",
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"42": "Education",
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"43": "Regional Integration",
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"44": "Jobs and Development",
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"45": "Competition Policy",
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"46": "Fragility, Conflict, and Violence",
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"47": "Urban Development",
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"48": "Pandemic Preparedness and COVID-19",
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"49": "Safety Nets and Cash Transfers",
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"50": "Financial Sector",
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"51": "Climate Change",
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"52": "Transport",
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"53": "COVID-19 Hub",
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"54": "Financial Stability",
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"55": "Gender",
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"56": "Natural Capital",
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"57": "Water in Agriculture",
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"58": "Taxes and Government Revenue",
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"59": "Labor Markets",
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"60": "Trade Facilitation and Logistics",
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"61": "Long-Term Finance",
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"62": "Teachers",
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"63": "Sanitation",
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"64": "Forests and Landscapes",
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"65": "Financial Integrity",
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"66": "Payment Systems",
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"67": "Social Inclusion",
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"68": "Health",
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"69": "Girls' Education",
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"70": "Credit Infrastructure",
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"71": "Social Sustainability and Inclusion",
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"72": "Trade",
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"73": "Financial Inclusion",
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"74": "Global Financing Facility for Women, Children and Adolescents",
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"75": "Sustainable Infrastructure Finance",
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"76": "Extractive Industries",
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"77": "Procurement for Development",
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"78": "Agriculture and Food",
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"79": "Water Supply",
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"80": "Disaster Risk Management",
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"81": "One Health",
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"82": "Environment",
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"83": "Digital Development",
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"84": "Agribusiness and Value Chains",
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"85": "Gas Flaring Reduction",
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"86": "Water Resources Management"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Agribusiness and Value Chains": 84,
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"Agriculture and Food": 78,
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"Biodiversity": 17,
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"COVID-19 Hub": 53,
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"Climate Change": 51,
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"Climate-Smart Agriculture": 25,
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"Community-Driven Development": 13,
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"Competition Policy": 45,
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"Competitiveness": 16,
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"Credit Infrastructure": 70,
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"Debt": 18,
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"Debt Relief": 40,
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"Digital Development": 83,
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"Disability Inclusion": 8,
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"Disaster Risk Management": 80,
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"Early Childhood Development": 10,
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"Education": 42,
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"Education and Technology": 23,
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"Energy": 6,
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"Environment": 82,
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"Extractive Industries": 76,
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"Financial Inclusion": 73,
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"Financial Integrity": 65,
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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"Universal Health Coverage": 21,
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"Water": 4,
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