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README.md

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-tags:
-- generated_from_keras_callback
-model-index:
-- name: GeoBERT
-  results: []
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-
-<!-- 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
-
-GeoBERT 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 with HuggingFace
-
-##### Load GeoBERT and its sub-word tokenizer :
-
-```python
-from transformers import AutoTokenizer, AutoModelForTokenClassification
-
-tokenizer = AutoTokenizer.from_pretrained("botryan96/GeoBERT")
-model = AutoModelForTokenClassification.from_pretrained("botryan96/GeoBERT")
-```