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NextQuAD trained on xlm-roberta

config.json

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+{
+  "_name_or_path": "deepset/xlm-roberta-large-squad2",
+  "architectures": [
+    "XLMRobertaForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "language": "english",
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "name": "XLMRoberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.12.5",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6155c0019930a057d4a09120d62db4530ee7641fb8b3192c85ebbb6ad0ff7032
+size 2239737325

result_dict.json

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+{
+    "best_val_loss": 0.548442452335533,
+    "epoch": [
+        0
+    ],
+    "train_loss": [
+        0.4031445865370374
+    ],
+    "val_loss": [
+        0.548442452335533
+    ]
+}

sentencepiece.bpe.model

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+oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
+size 5069051

special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "do_lower_case": false, "model_max_length": 512, "special_tokens_map_file": "germanQA/saved_models/xlm-roberta-large-squad2/special_tokens_map.json", "full_tokenizer_file": null, "name_or_path": "deepset/xlm-roberta-large-squad2", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"}