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CodeBERT model trained on violent-python dataset with block-, function- and line-level samples combined.
Batch-size = 16, source and target token length = 256.

config.json

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+{
+  "attention_probs_dropout_prob": 0.1,
+  "finetuning_task": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_labels": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "output_past": true,
+  "pruned_heads": {},
+  "torchscript": false,
+  "type_vocab_size": 1,
+  "use_bfloat16": false,
+  "vocab_size": 50265
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f66f5d476fc68aed5d315caacd01bcf0d0ffd8eae274514d63f4149d647130a3
+size 706916066