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README.md

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+---
+license: mit
+language:
+- de
+metrics:
+- accuracy
+tags:
+- twitter
+---
+
+# T-GBERT
+
+This is a [GBERT-base](https://huggingface.co/deepset/gbert-base) with continued pretraining
+on roughly 33 million German X/Twitter deduplicated posts from 2020. The pretraining is follows the task-adaptive pretraining setup suggested by
+[Gururangan et al. (2020)](https://aclanthology.org/2020.acl-main.740). In total, the model was trained for 10 epochs. I am sharing this model as
+it might be useful to some of you and initial result suggest (some) improvements compared to [GBERT-base](https://huggingface.co/deepset/gbert-base)
+(which is a common choice for supervised fine-tuning).
+
+## Performance
+
+|            | [GermEval-2017](https://sites.google.com/view/germeval2017-absa/home)<br>(subtask B, synchronic test set)| [SB10k](https://aclanthology.org/W17-1106/) |
+|:----------:|:-------------:|:-----:|
+| GBERT-base |     79.77%     | 82.29% |
+|   T-GBERT  |     81.50%     | 82.88% |
+
+*Results report the accuracy (micro F1-score) on the test set of the respective dataset. The results represent the average of five runs
+with different seeds for data shuffling and parameter initialization.*
+
+## Preprocessing
+Weblinks in posts were replaced by 'https' and user mentions were replaced by '@user'.
+<br><br>
+
+
+

config.json

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+{
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31102
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "pad_token_id": 0,
+  "transformers_version": "4.38.1"
+}

model.safetensors

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+size 439864976

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
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+      "lstrip": false,
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": false,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}