Training in progress, step 90

.gitignore

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config.json

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+  "_name_or_path": "Mathking/bert-base-german-cased-gnad10",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
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+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "amerika",
+    "1": "asien",
+    "2": "finanzen",
+    "3": "innenpolitik",
+    "4": "sportschau",
+    "5": "unternehmen",
+    "6": "verbraucher"
+  },
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+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.21.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30000
+}

pytorch_model.bin

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "name_or_path": "Mathking/bert-base-german-cased-gnad10",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
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+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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