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setfit-paraphrase-mpnet-base-v2-13ClassesDesc

Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Model card Files Community
lgsilvaesilva commited on
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  1. README.md +143 -0
  2. model.safetensors +1 -1
  3. model_head.pkl +2 -2
  4. tokenizer.json +14 -2
README.md CHANGED
@@ -194,6 +194,149 @@ preds = model("As of June 2022, the level of food insecurity in the country was
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  | 1.4. Food environments: Examines the conditions—physical, economic, political, social, and cultural—that influence the availability, affordability, and appeal of healthy foods. | 11 |
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  | 6.3.3 Awareness and use of the evidence-based / agrifood systems approach: Encourages long-term, integrated planning for agrifood systems, guided by robust data, stakeholder consensus, and strategic foresight. | 30 |
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  ### Framework Versions
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  - Python: 3.11.11
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  - SetFit: 1.1.1
 
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  | 1.4. Food environments: Examines the conditions—physical, economic, political, social, and cultural—that influence the availability, affordability, and appeal of healthy foods. | 11 |
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  | 6.3.3 Awareness and use of the evidence-based / agrifood systems approach: Encourages long-term, integrated planning for agrifood systems, guided by robust data, stakeholder consensus, and strategic foresight. | 30 |
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+ ### Training Hyperparameters
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+ - batch_size: (8, 8)
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+ - num_epochs: (1, 1)
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+ - max_steps: -1
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+ - sampling_strategy: oversampling
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+ - body_learning_rate: (2e-05, 1e-05)
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+ - head_learning_rate: 0.01
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+ - loss: CosineSimilarityLoss
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+ - distance_metric: cosine_distance
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+ - margin: 0.25
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+ - end_to_end: False
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+ - use_amp: False
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+ - warmup_proportion: 0.1
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+ - l2_weight: 0.01
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+ - seed: 42
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+ - eval_max_steps: -1
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+ - load_best_model_at_end: True
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+
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+ ### Training Results
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:------:|:----:|:-------------:|:---------------:|
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+ | 0.0002 | 1 | 0.2741 | - |
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+ | 0.0083 | 50 | 0.2208 | - |
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+ | 0.0167 | 100 | 0.2153 | - |
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+ | 0.0250 | 150 | 0.1977 | - |
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+ | 0.0333 | 200 | 0.2096 | - |
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+ | 0.0417 | 250 | 0.1936 | - |
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+ | 0.0500 | 300 | 0.1678 | - |
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+ | 0.0583 | 350 | 0.1477 | - |
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+ | 0.0667 | 400 | 0.1357 | - |
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+ | 0.0750 | 450 | 0.1304 | - |
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+ | 0.0833 | 500 | 0.1411 | - |
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+ | 0.0917 | 550 | 0.1221 | - |
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+ | 0.1000 | 600 | 0.1265 | - |
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+ | 0.1084 | 650 | 0.113 | - |
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+ | 0.1167 | 700 | 0.1053 | - |
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+ | 0.1250 | 750 | 0.0871 | - |
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+ | 0.1334 | 800 | 0.0896 | - |
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+ | 0.1417 | 850 | 0.0786 | - |
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+ | 0.1500 | 900 | 0.0921 | - |
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+ | 0.1584 | 950 | 0.0878 | - |
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+ | 0.1667 | 1000 | 0.075 | - |
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+ | 0.1750 | 1050 | 0.0985 | - |
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+ | 0.1834 | 1100 | 0.0984 | - |
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+ | 0.1917 | 1150 | 0.0848 | - |
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+ | 0.2000 | 1200 | 0.0923 | - |
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+ | 0.2084 | 1250 | 0.0894 | - |
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+ | 0.2167 | 1300 | 0.0727 | - |
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+ | 0.2250 | 1350 | 0.0807 | - |
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+ | 0.2334 | 1400 | 0.0715 | - |
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+ | 0.2417 | 1450 | 0.0728 | - |
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+ | 0.2500 | 1500 | 0.056 | - |
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+ | 0.2584 | 1550 | 0.0683 | - |
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+ | 0.2667 | 1600 | 0.0729 | - |
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+ | 0.2750 | 1650 | 0.0625 | - |
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+ | 0.2834 | 1700 | 0.0582 | - |
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+ | 0.2917 | 1750 | 0.0483 | - |
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+ | 0.3001 | 1800 | 0.0449 | - |
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+ | 0.3084 | 1850 | 0.0695 | - |
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+ | 0.3167 | 1900 | 0.0626 | - |
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+ | 0.3251 | 1950 | 0.0596 | - |
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+ | 0.3334 | 2000 | 0.072 | - |
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+ | 0.3417 | 2050 | 0.0623 | - |
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+ | 0.3501 | 2100 | 0.0689 | - |
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+ | 0.3584 | 2150 | 0.0514 | - |
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+ | 0.3667 | 2200 | 0.0646 | - |
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+ | 0.3751 | 2250 | 0.0495 | - |
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+ | 0.3834 | 2300 | 0.057 | - |
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+ | 0.3917 | 2350 | 0.0697 | - |
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+ | 0.4001 | 2400 | 0.0501 | - |
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+ | 0.4084 | 2450 | 0.0503 | - |
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+ | 0.4167 | 2500 | 0.0469 | - |
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+ | 0.4251 | 2550 | 0.0418 | - |
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+ | 0.4334 | 2600 | 0.0399 | - |
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+ | 0.4417 | 2650 | 0.0555 | - |
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+ | 0.4501 | 2700 | 0.0597 | - |
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+ | 0.4584 | 2750 | 0.0545 | - |
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+ | 0.4667 | 2800 | 0.0552 | - |
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+ | 0.4751 | 2850 | 0.0454 | - |
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+ | 0.4834 | 2900 | 0.048 | - |
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+ | 0.4917 | 2950 | 0.0524 | - |
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+ | 0.5001 | 3000 | 0.0512 | - |
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+ | 0.5084 | 3050 | 0.0594 | - |
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+ | 0.5168 | 3100 | 0.0609 | - |
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+ | 0.5251 | 3150 | 0.0479 | - |
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+ | 0.5334 | 3200 | 0.0439 | - |
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+ | 0.5418 | 3250 | 0.0519 | - |
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+ | 0.5501 | 3300 | 0.0507 | - |
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+ | 0.5584 | 3350 | 0.054 | - |
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+ | 0.5668 | 3400 | 0.0457 | - |
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+ | 0.5751 | 3450 | 0.0587 | - |
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+ | 0.5834 | 3500 | 0.0484 | - |
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+ | 0.5918 | 3550 | 0.0531 | - |
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+ | 0.6001 | 3600 | 0.0592 | - |
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+ | 0.6084 | 3650 | 0.0583 | - |
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+ | 0.6168 | 3700 | 0.0374 | - |
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+ | 0.6251 | 3750 | 0.0424 | - |
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+ | 0.6334 | 3800 | 0.049 | - |
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+ | 0.6418 | 3850 | 0.0406 | - |
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+ | 0.6501 | 3900 | 0.0476 | - |
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+ | 0.6584 | 3950 | 0.0476 | - |
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+ | 0.6668 | 4000 | 0.053 | - |
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+ | 0.6751 | 4050 | 0.0431 | - |
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+ | 0.6834 | 4100 | 0.0539 | - |
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+ | 0.6918 | 4150 | 0.0456 | - |
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+ | 0.7001 | 4200 | 0.0468 | - |
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+ | 0.7085 | 4250 | 0.0416 | - |
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+ | 0.7168 | 4300 | 0.0438 | - |
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+ | 0.7251 | 4350 | 0.0558 | - |
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+ | 0.7335 | 4400 | 0.0514 | - |
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+ | 0.7418 | 4450 | 0.0464 | - |
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+ | 0.7501 | 4500 | 0.0445 | - |
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+ | 0.7585 | 4550 | 0.0439 | - |
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+ | 0.7668 | 4600 | 0.0466 | - |
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+ | 0.7751 | 4650 | 0.053 | - |
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+ | 0.7835 | 4700 | 0.0638 | - |
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+ | 0.7918 | 4750 | 0.0438 | - |
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+ | 0.8001 | 4800 | 0.0481 | - |
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+ | 0.8085 | 4850 | 0.0431 | - |
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+ | 0.8168 | 4900 | 0.0505 | - |
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+ | 0.8251 | 4950 | 0.055 | - |
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+ | 0.8335 | 5000 | 0.0322 | - |
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+ | 0.8418 | 5050 | 0.0471 | - |
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+ | 0.8501 | 5100 | 0.0462 | - |
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+ | 0.8585 | 5150 | 0.0458 | - |
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+ | 0.8668 | 5200 | 0.0446 | - |
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+ | 0.8751 | 5250 | 0.0487 | - |
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+ | 0.8835 | 5300 | 0.0385 | - |
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+ | 0.8918 | 5350 | 0.0385 | - |
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+ | 0.9002 | 5400 | 0.0467 | - |
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+ | 0.9085 | 5450 | 0.0415 | - |
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+ | 0.9168 | 5500 | 0.0345 | - |
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+ | 0.9252 | 5550 | 0.0414 | - |
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+ | 0.9335 | 5600 | 0.0475 | - |
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+ | 0.9418 | 5650 | 0.0472 | - |
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+ | 0.9502 | 5700 | 0.0568 | - |
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+ | 0.9585 | 5750 | 0.0376 | - |
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+ | 0.9668 | 5800 | 0.0477 | - |
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+ | 0.9752 | 5850 | 0.0487 | - |
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+ | 0.9835 | 5900 | 0.0354 | - |
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+ | 0.9918 | 5950 | 0.0433 | - |
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+ | 1.0 | 5999 | - | 0.2466 |
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+
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  ### Framework Versions
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  - Python: 3.11.11
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  - SetFit: 1.1.1
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tokenizer.json CHANGED
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