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Training completed

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: xlm-roberta-base
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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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+ - f1
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+ model-index:
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+ - name: xlm-roberta-base-finetuned-panx-Indo
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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: F1
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+ type: f1
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+ value: 0.83694517516389
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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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+ # xlm-roberta-base-finetuned-panx-Indo
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the id_nergrit_corpus dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1919
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+ - F1: 0.8369
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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: 5e-05
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+ - train_batch_size: 24
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+ - eval_batch_size: 24
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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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.3999 | 1.0 | 523 | 0.2013 | 0.8147 |
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+ | 0.1624 | 2.0 | 1046 | 0.1942 | 0.8249 |
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+ | 0.1097 | 3.0 | 1569 | 0.1919 | 0.8369 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "xlm-roberta-base",
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+ "architectures": [
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+ "XLMRobertaForTokenClassification"
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+ ],
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "id2label": {
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+ "0": "B-CRD",
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+ "layer_norm_eps": 1e-05,
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