upload

CEBinaryClassificationEvaluator_Quora-dev_results.csv

@@ -0,0 +1,15 @@
+epoch,steps,Accuracy,Accuracy_Threshold,F1,F1_Threshold,Precision,Recall,Average_Precision
+0,5000,0.8608639203700198,0.2873433232307434,0.8098558473933306,0.19083455204963684,0.7614130434782609,0.8648815495022764,0.8629331317298123
+0,10000,0.863839225338779,0.25037556886672974,0.8119228437979106,0.12073762714862823,0.7546394485683987,0.8786171772513311,0.8678734374248867
+0,15000,0.8680587487490194,0.2262679636478424,0.8200071968333933,0.11036892235279083,0.7682556806688693,0.8792345088355583,0.875549687970233
+0,20000,0.8685456168348165,0.20787009596824646,0.8190316830962862,0.12376940995454788,0.7747041012936967,0.8687398719036963,0.8764299796079794
+0,25000,0.8720077898893728,0.3845294713973999,0.8250813155041562,0.2559159994125366,0.7759499694106451,0.8808550042441546,0.8833998414872404
+0,30000,0.8729815260609667,0.5238280296325684,0.8255852051403401,0.3320024907588959,0.781461061337009,0.8749903541939964,0.878249009917573
+0,-1,0.8710611019447675,0.4382350444793701,0.8225952648562416,0.149741068482399,0.7758172616605116,0.8753761864341384,0.8821009813520877
+1,5000,0.8723864650672148,0.13579325377941132,0.8250017981730562,0.046766698360443115,0.772546642419344,0.8850991588857164,0.8772769680139632
+1,10000,0.8706012820859592,0.17663632333278656,0.8243606757289911,0.04282882809638977,0.7701380511995711,0.8867968207423412,0.8717299987211413
+1,15000,0.8711963430797112,0.062239423394203186,0.8229883392482075,0.025501983240246773,0.775366769020812,0.876842348946678,0.88006993940756
+1,20000,0.8719266452084066,0.03155897557735443,0.8244302380178423,0.010280131362378597,0.7749185225420967,0.8807006713480978,0.8812910141874843
+1,25000,0.8726028508831246,0.03645790368318558,0.8253768844221104,0.03082387149333954,0.7918468628146047,0.8618720580291689,0.8816145619414946
+1,30000,0.8732249601038652,0.03989178314805031,0.8268535595721136,0.029114533215761185,0.7920288318846724,0.8648815495022764,0.8793008086700131
+1,-1,0.8735765870547185,0.05718168243765831,0.8270970543533329,0.018996555358171463,0.7787393526405452,0.8818581680685238,0.8779853764105872

README.md

@@ -0,0 +1,18 @@
+# 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.
+
+## 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
+
+Pre-trained models can be used like this:
+```
+from sentence_transformers import CrossEncoder
+model = CrossEncoder('model_name')
+scores = model.predict([('Question 1', 'Question 2'), ('Question 3', 'Question 4')])
+```
+
+You can use this model also without sentence_transformers and by just using Transformers ``AutoModel`` class

config.json

@@ -0,0 +1,28 @@
+{
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "type_vocab_size": 1,
+  "vocab_size": 50265
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbebb63aa533e7d3b68b2e0d205287523fff83ab36e434003d55f855e699acc6
+size 498676169

special_tokens_map.json

@@ -0,0 +1 @@
+{"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}}

tokenizer_config.json

@@ -0,0 +1 @@
+{"model_max_length": 512, "special_tokens_map_file": "final-models/ce-roberta-base-mnli/special_tokens_map.json", "full_tokenizer_file": null}