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bryanahusna/my-nergrit-model

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: indolem/indobert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - id_nergrit_corpus
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: my_nergrit_model
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: id_nergrit_corpus
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+ type: id_nergrit_corpus
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+ config: ner
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+ split: validation
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+ args: ner
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.811461318051576
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+ - name: Recall
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+ type: recall
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+ value: 0.8397580358201874
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+ - name: F1
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+ type: f1
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+ value: 0.8253672184658428
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.947162775616083
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # my_nergrit_model
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+
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+ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the id_nergrit_corpus dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1786
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+ - Precision: 0.8115
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+ - Recall: 0.8398
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+ - F1: 0.8254
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+ - Accuracy: 0.9472
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5063 | 1.0 | 784 | 0.1926 | 0.7911 | 0.8243 | 0.8074 | 0.9418 |
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+ | 0.164 | 2.0 | 1568 | 0.1786 | 0.8115 | 0.8398 | 0.8254 | 0.9472 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "indolem/indobert-base-uncased",
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+ "architectures": [
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+ "BertForTokenClassification"
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+ ],
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tokenizer.json ADDED
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