Training complete

README.md

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+---
+license: mit
+base_model: cahya/bert-base-indonesian-1.5G
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: belajarner_bert_case
+  results: []
+---
+
+<!-- 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. -->
+
+# belajarner_bert_case
+
+This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3302
+- Precision: 0.8314
+- Recall: 0.8484
+- F1: 0.8398
+- Accuracy: 0.9471
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1904        | 1.0   | 1567  | 0.2090          | 0.7825    | 0.8298 | 0.8054 | 0.9385   |
+| 0.1195        | 2.0   | 3134  | 0.2141          | 0.8312    | 0.8237 | 0.8274 | 0.9446   |
+| 0.0772        | 3.0   | 4701  | 0.2200          | 0.8220    | 0.8427 | 0.8322 | 0.9457   |
+| 0.0463        | 4.0   | 6268  | 0.2636          | 0.8158    | 0.8498 | 0.8324 | 0.9446   |
+| 0.0342        | 5.0   | 7835  | 0.2878          | 0.8351    | 0.8392 | 0.8372 | 0.9456   |
+| 0.0223        | 6.0   | 9402  | 0.3066          | 0.8267    | 0.8414 | 0.8340 | 0.9454   |
+| 0.0139        | 7.0   | 10969 | 0.3250          | 0.8302    | 0.8476 | 0.8388 | 0.9466   |
+| 0.0096        | 8.0   | 12536 | 0.3302          | 0.8314    | 0.8484 | 0.8398 | 0.9471   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "cahya/bert-base-indonesian-1.5G",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-CRD",
+    "1": "B-DAT",
+    "2": "B-EVT",
+    "3": "B-FAC",
+    "4": "B-GPE",
+    "5": "B-LAN",
+    "6": "B-LAW",
+    "7": "B-LOC",
+    "8": "B-MON",
+    "9": "B-NOR",
+    "10": "B-ORD",
+    "11": "B-ORG",
+    "12": "B-PER",
+    "13": "B-PRC",
+    "14": "B-PRD",
+    "15": "B-QTY",
+    "16": "B-REG",
+    "17": "B-TIM",
+    "18": "B-WOA",
+    "19": "I-CRD",
+    "20": "I-DAT",
+    "21": "I-EVT",
+    "22": "I-FAC",
+    "23": "I-GPE",
+    "24": "I-LAN",
+    "25": "I-LAW",
+    "26": "I-LOC",
+    "27": "I-MON",
+    "28": "I-NOR",
+    "29": "I-ORD",
+    "30": "I-ORG",
+    "31": "I-PER",
+    "32": "I-PRC",
+    "33": "I-PRD",
+    "34": "I-QTY",
+    "35": "I-REG",
+    "36": "I-TIM",
+    "37": "I-WOA",
+    "38": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "B-DAT": 1,
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+    "B-FAC": 3,
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+    "I-FAC": 22,
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+    "I-LAN": 24,
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+    "I-PER": 31,
+    "I-PRC": 32,
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+    "I-QTY": 34,
+    "I-REG": 35,
+    "I-TIM": 36,
+    "I-WOA": 37,
+    "O": 38
+  },
+  "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": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

model.safetensors

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runs/Feb19_05-26-34_280a5290dce0/events.out.tfevents.1708320396.280a5290dce0.2510.0

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
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tokenizer_config.json

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+  "do_lower_case": true,
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+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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