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README.md

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+---
+datasets:
+- quora
+language: en
+license: mit
+pipeline_tag: text-classification
+tags:
+- roberta
+- text-classification
+---
+# Cross-Encoder for Quora Duplicate Questions Detection
+
+This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
+
+This model uses [roberta-large](https://huggingface.co/roberta-large).
+
+## Training Data
+
+This model was trained on the [Quora Duplicate Questions](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) dataset.
+
+The model will predict a score between 0 and 1: How likely the two given questions are duplicates.
+
+Note: The model is not suitable to estimate the similarity of questions, e.g. the two questions "How to learn Java" and "How to learn Python" will result in a rahter low score, as these are not duplicates.
+
+## Usage and Performance
+
+The trained model can be used like this:
+
+```python
+from sentence_transformers import CrossEncoder
+
+model = CrossEncoder('model_name')
+scores = model.predict([('Question 1', 'Question 2'), ('Question 3', 'Question 4')])
+
+print(scores)
+```

config.json

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+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
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+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
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+  "hidden_size": 1024,
+  "id2label": {
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+  "num_hidden_layers": 24,
+  "pad_token_id": 1,
+  "type_vocab_size": 1,
+  "vocab_size": 50265
+}

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special_tokens_map.json

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tokenizer_config.json

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+    "model_max_length": 512,
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+}