First version.

README.md

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+---
+language: tr
+datasets:
+    - tremo
+---
+
+# BERTurk fine-tuned on emotion classification
+
+This model is [BERTurk cased](https://huggingface.co/dbmdz/bert-base-turkish-cased)
+model finetuned on the [TREMO](http://demir.cs.deu.edu.tr/TREMO) data
+set for Turkis emotion classification.
+
+The macro-average F1 score of the model is approximately 94% on a
+randomly set aside development set of 2k instances.

config.json

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+{
+  "_name_or_path": "final-model",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Anger",
+    "1": "Disgust",
+    "2": "Fear",
+    "3": "Happy",
+    "4": "Sadness",
+    "5": "Surprise"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Anger": 0,
+    "Disgust": 1,
+    "Fear": 2,
+    "Happy": 3,
+    "Sadness": 4,
+    "Surprise": 5
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

pytorch_model.bin

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special_tokens_map.json

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

tf_model.h5

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tokenizer_config.json

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+{
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "name_or_path": "dbmdz/bert-base-turkish-cased",
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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