Upload AgriSagot Philippine agricultural BERT model

README.md

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+---
+tags:
+- agriculture
+- bert
+- philippine-agriculture
+- crop-disease
+- recommendation
+- agrisagot
+language:
+- en
+license: mit
+---
+
+# AgriSagot BERT - Philippine Agricultural Recommender
+
+This model is fine-tuned on Philippine agricultural data for crop disease and pesticide recommendations, specifically designed for the AgriSagot application.
+
+## Model Description
+
+- **Base Model**: BERT-base-uncased  
+- **Training Data**: Philippine registered agricultural products (as of August 2025)
+- **Use Case**: Agricultural product recommendations based on crop and disease
+- **Language**: English
+- **Country**: Philippines
+- **Application**: AgriSagot - Smart Agricultural Advisory System
+
+## Usage
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+model = AutoModel.from_pretrained("Hayme/agrisago-bert")
+tokenizer = AutoTokenizer.from_pretrained("Hayme/agrisago-bert")
+
+# Use for generating embeddings
+inputs = tokenizer("rice blast treatment", return_tensors="pt")
+outputs = model(**inputs)
+embeddings = outputs.last_hidden_state.mean(dim=1)
+```
+
+## API Usage
+
+```javascript
+// In your AgriSagot API
+const response = await hf.featureExtraction({
+    model: 'Hayme/agrisago-bert',
+    inputs: 'rice brown planthopper treatment'
+});
+```
+
+## Training Data
+
+Trained on the official "UPDATED LIST OF REGISTERED PRODUCTS As of August 31, 2025" from Philippine regulatory authorities, containing comprehensive information about:
+
+- Agricultural pesticides
+- Fertilizers  
+- Plant growth regulators
+- Crop protection products
+- Target crops and pests/diseases
+- Active ingredients and formulations
+
+## Intended Use
+
+- Crop disease identification and treatment recommendations
+- Agricultural product recommendations for Philippine farmers
+- Pesticide matching for specific crop-disease combinations
+- Integration with AgriSagot mobile and web applications
+- Philippine agricultural advisory and extension services
+
+## Performance
+
+This model understands Philippine-specific agricultural contexts including:
+- Local crop varieties (rice, corn, tomato, etc.)
+- Common Philippine pests and diseases
+- Available agricultural products in the Philippine market
+- Regulatory-approved treatment options
+
+## Limitations
+
+- Trained specifically on Philippine agricultural data
+- Recommendations should be verified with local agricultural experts
+- Not suitable for other countries' agricultural systems without adaptation
+
+## Citation
+
+If you use this model, please cite:
+```
+AgriSagot BERT Model (2025)
+Trained on Philippine Agricultural Product Database
+Available at: https://huggingface.co/Hayme/agrisago-bert
+```

config.json

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+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.57.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:019aa07f3b343bd542efdf5b843a91d764fc03bd49ef07db870f13be5164bd21
+size 437951328

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}