Upload 5 files

bertram_config.json

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+{"py/object": "bertram.BertramConfig", "transformer_cls": "deberta", "output_size": 768, "mode": "add", "ngram_vocab_size": 712}

config.json

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+{
+  "_name_or_path": "./outputs/DeBERTa_fused",
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "c2p",
+    "p2c"
+  ],
+  "position_biased_input": false,
+  "relative_attention": true,
+  "transformers_version": "4.24.0",
+  "type_vocab_size": 0,
+  "vocab_size": 50265
+}

input_processor.json

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+{"py/object": "input_processor.InputProcessor", "py/state": {"model_cls": "deberta", "bert_model": "microsoft/deberta-base", "word_embeddings_file": "./fcm/wordEmbeddings/glove.6B.300d.txt", "word_embeddings_format": "text", "train_files": ["./training/train.bucket23.txt", "./training/train.bucket17.txt", "./training/train.bucket2.txt", "./training/train.bucket1.txt", "./training/train.bucket9.txt", "./training/train.bucket8.txt", "./training/train.bucket10.txt", "./training/train.bucket24.txt", "./training/train.bucket12.txt", "./training/train.bucket22.txt", "./training/train.bucket20.txt", "./training/train.bucket21.txt", "./training/train.bucket0.txt", "./training/train.bucket18.txt", "./training/train.bucket15.txt", "./training/train.bucket5.txt", "./training/train.bucket19.txt", "./training/train.bucket11.txt", "./training/train.bucket7.txt", "./training/train.bucket13.txt", "./training/train.bucket6.txt", "./training/train.bucket16.txt", "./training/train.bucket4.txt", "./training/train.bucket14.txt", "./training/train.bucket3.txt"], "vocab_file": "./outputs/DeBERTa_fused/input_processor.json.vocab", "vector_size": 768, "ngram_threshold": 4, "nmin": 3, "nmax": 5, "ngram_dropout": 0.1, "min_word_count": 100, "max_copies": 5, "smin": 4, "smax": 32, "max_seq_length": 96, "mode": null, "form_only": false, "sep_symbol": ":", "train_file_idx": 0}}

input_processor.json.vocab

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pytorch_model.bin

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