Create README.md

README.md

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+---
+tags:
+- generated_from_keras_callback
+model-index:
+- name: GeoBERT_NER
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# GeoBERT_NER
+
+GeoBERT_NER is a NER model that was fine-tuned from SciBERT on the Geoscientific Corpus dataset.
+The model was trained on the Labeled Geoscientific Corpus dataset (~1 million sentences).
+
+
+## Intended uses
+
+The NER product in this model has a goal to identify four main semantic types or categories related to Geosciences. 
+
+1. GeoPetro for any entities that belong to all terms in Geosciences
+2. GeoMeth for all tools or methods associated with Geosciences
+3. GeoLoc to identify geological locations
+4. GeoTime for identifying the geological time scale entities
+
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 14000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: mixed_float16
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- TensorFlow 2.10.0
+- Datasets 2.4.0
+- Tokenizers 0.12.1
+
+## Model performances (metric: seqeval)
+
+entity|precision|recall|f1
+-|-|-|-
+GeoLoc  |0.9727|0.9591|0.9658 
+GeoMeth |0.9433|0.9447|0.9445
+GeoPetro|0.9767|0.9745|0.9756
+GeoTime |0.9695|0.9666|0.9680
+
+## How to use GeoBERT_NER with HuggingFace
+
+##### Load GeoBERT and its sub-word tokenizer :
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("botryan96/GeoBERT_NER")
+model = AutoModelForTokenClassification.from_pretrained("botryan96/GeoBERT_NER")
+```