Finetuned with data v4

README.md

@@ -1,3 +1,35 @@
----
-license: apache-2.0
----
+---
+language:
+- en
+widget:
+- text: "We explores the impact of initial and boundary conditions on simulating an extra-tropical cyclones in the North Atlantic Ocean, employing the Weather Research and Forecasting (WRF) model. The study assesses cyclone trajectory and synoptic patterns against real-world observations, finding that the WRF model effectively replicates Gong's entire lifecycle, including its intensification phase. It was observed that both the genesis of the cyclone and its Q-Vector—a meteorological vector that indicates the potential for cyclogenesis—are significantly influenced by the initial conditions set in the model."
+  example_title: "LABEL_15 (Severe Storms)"
+---
+## Label Mapping
+
+The model classifies inputs into the following categories, each represented by a unique label ID:
+
+| Category                           | ID |
+|------------------------------------|----|
+| Agriculture                        | 0  |
+| Air Quality                        | 1  |
+| Atmospheric/Ocean Indicators       | 2  |
+| Cryospheric Indicators             | 3  |
+| Droughts                           | 4  |
+| Earthquakes                        | 5  |
+| Ecosystems                         | 6  |
+| Energy Production/Use              | 7  |
+| Environmental Impacts              | 8  |
+| Floods                             | 9  |
+| Greenhouse Gases                   | 10 |
+| Habitat Conversion/Fragmentation   | 11 |
+| Heat                               | 12 |
+| Land Surface/Agriculture Indicators| 13 |
+| Public Health                      | 14 |
+| Severe Storms                      | 15 |
+| Sun-Earth Interactions             | 16 |
+| Validation                         | 17 |
+| Volcanic Eruptions                 | 18 |
+| Water Quality                      | 19 |
+| Wildfires                          | 20 |
+

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.2,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.2,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14",
+    "15": "LABEL_15",
+    "16": "LABEL_16",
+    "17": "LABEL_17",
+    "18": "LABEL_18",
+    "19": "LABEL_19",
+    "20": "LABEL_20"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "LABEL_13": 13,
+    "LABEL_14": 14,
+    "LABEL_15": 15,
+    "LABEL_16": 16,
+    "LABEL_17": 17,
+    "LABEL_18": 18,
+    "LABEL_19": 19,
+    "LABEL_2": 2,
+    "LABEL_20": 20,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9103d5f3711f8f27a3d1bf6187795764f936dbb4c0ce3c1aab4f24e093989007
+size 438061937