add model

.gitignore

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+checkpoint-*/

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- null
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model_index:
+- name: electra-srb-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.9509610737256943
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# electra-srb-ner
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2686
+- Precision: 0.8132
+- Recall: 0.7889
+- F1: 0.8009
+- Accuracy: 0.9510
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 207  | 0.2887          | 0.7392    | 0.6269 | 0.6784 | 0.9221   |
+| No log        | 2.0   | 414  | 0.2076          | 0.7690    | 0.7147 | 0.7409 | 0.9397   |
+| 0.2949        | 3.0   | 621  | 0.2011          | 0.7698    | 0.7583 | 0.7640 | 0.9441   |
+| 0.2949        | 4.0   | 828  | 0.2077          | 0.7600    | 0.7807 | 0.7702 | 0.9451   |
+| 0.089         | 5.0   | 1035 | 0.2198          | 0.7884    | 0.7684 | 0.7783 | 0.9465   |
+| 0.089         | 6.0   | 1242 | 0.2437          | 0.7885    | 0.7824 | 0.7854 | 0.9474   |
+| 0.089         | 7.0   | 1449 | 0.2394          | 0.7986    | 0.7970 | 0.7978 | 0.9511   |
+| 0.0322        | 8.0   | 1656 | 0.2675          | 0.8135    | 0.7775 | 0.7951 | 0.9497   |
+| 0.0322        | 9.0   | 1863 | 0.2832          | 0.8161    | 0.7798 | 0.7975 | 0.9508   |
+| 0.0141        | 10.0  | 2070 | 0.2686          | 0.8132    | 0.7889 | 0.8009 | 0.9510   |
+
+
+### Framework versions
+
+- Transformers 4.9.2
+- Pytorch 1.9.0
+- Datasets 1.11.0
+- Tokenizers 0.10.1

config.json

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+{
+  "_name_or_path": "Aleksandar/electra-srb-oscar",
+  "architectures": [
+    "ElectraForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "embedding_size": 768,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.9.2",
+  "type_vocab_size": 2,
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "Aleksandar/electra-srb-oscar", "tokenizer_class": "ElectraTokenizer"}

training_args.bin

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