Create README.md

README.md

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+---
+tags:
+- generated_from_keras_callback
+model-index:
+- name: GeoBERT
+  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_Analyzer
+
+GeoBERT_Analyzer is a Text Classification model that was fine-tuned from GeoBERT on the Geoscientific Corpus dataset.
+The model was trained on the Labeled Geoscientific & Non-Geosceintific Corpus dataset (21416 x 2 sentences).
+
+
+## Intended uses
+
+The train aims to make the Language Model have the ability to distinguish between Geoscience and Non – Geoscience (General) corpus
+
+
+### 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
+-|-|-|-
+General   |0.9976|0.9980|0.9978 
+Geoscience|0.9980|0.9984|0.9982
+
+## How to use GeoBERT with HuggingFace
+
+##### Load GeoBERT and its sub-word tokenizer :
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("botryan96/GeoBERT_analyzer")
+model = AutoModelForTokenClassification.from_pretrained("botryan96/GeoBERT_analyzer")
+```