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: distilbert-srb-ner-setimes
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.962385099177552
+---
+
+<!-- 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. -->
+
+# distilbert-srb-ner-setimes
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1354
+- Precision: 0.8
+- Recall: 0.8319
+- F1: 0.8156
+- Accuracy: 0.9624
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 207  | 0.2206          | 0.7029    | 0.7267 | 0.7146 | 0.9384   |
+| No log        | 2.0   | 414  | 0.1582          | 0.7449    | 0.7813 | 0.7627 | 0.9532   |
+| 0.2358        | 3.0   | 621  | 0.1449          | 0.7756    | 0.8171 | 0.7958 | 0.9579   |
+| 0.2358        | 4.0   | 828  | 0.1382          | 0.7903    | 0.8329 | 0.8110 | 0.9609   |
+| 0.0895        | 5.0   | 1035 | 0.1354          | 0.8       | 0.8319 | 0.8156 | 0.9624   |
+
+
+### 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/distilbert-srb-base-cased-oscar",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "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,
+  "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
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.9.2",
+  "vocab_size": 50257
+}

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": false, "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/distilbert-srb-base-cased-oscar", "tokenizer_class": "DistilBertTokenizer"}

training_args.bin

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