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README.md
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---
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license: mit
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base_model: FacebookAI/xlm-roberta-large
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tags:
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- generated_from_trainer
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model-index:
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- name: xlm-roberta-large-finetuned-ner-vlsp2021-3090-1July-1
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results: []
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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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# xlm-roberta-large-finetuned-ner-vlsp2021-3090-1July-1
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.1332
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- eval_ATETIME: {'precision': 0.8748768472906404, 'recall': 0.8862275449101796, 'f1': 0.8805156172533465, 'number': 1002}
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- eval_DDRESS: {'precision': 0.7837837837837838, 'recall': 1.0, 'f1': 0.8787878787878788, 'number': 29}
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- eval_ERSON: {'precision': 0.9496365524402908, 'recall': 0.9631384939441812, 'f1': 0.9563398692810458, 'number': 1899}
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- eval_ERSONTYPE: {'precision': 0.7142857142857143, 'recall': 0.7602339181286549, 'f1': 0.7365439093484419, 'number': 684}
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- eval_HONENUMBER: {'precision': 1.0, 'recall': 0.8888888888888888, 'f1': 0.9411764705882353, 'number': 9}
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- eval_ISCELLANEOUS: {'precision': 0.5521472392638037, 'recall': 0.5660377358490566, 'f1': 0.5590062111801242, 'number': 159}
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- eval_MAIL: {'precision': 1.0, 'recall': 0.9803921568627451, 'f1': 0.99009900990099, 'number': 51}
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- eval_OCATION: {'precision': 0.8478731074260994, 'recall': 0.9039200614911607, 'f1': 0.875, 'number': 1301}
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- eval_P: {'precision': 0.9090909090909091, 'recall': 0.9090909090909091, 'f1': 0.9090909090909091, 'number': 11}
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- eval_RL: {'precision': 0.5789473684210527, 'recall': 0.7333333333333333, 'f1': 0.6470588235294117, 'number': 15}
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- eval_RODUCT: {'precision': 0.7018739352640545, 'recall': 0.6592, 'f1': 0.6798679867986799, 'number': 625}
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- eval_overall_precision: 0.8469
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- eval_overall_recall: 0.8683
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- eval_overall_f1: 0.8575
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- eval_overall_accuracy: 0.9793
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- eval_runtime: 38.9411
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- eval_samples_per_second: 64.919
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- eval_steps_per_second: 16.23
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- epoch: 7.0
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- step: 22841
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 4
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- eval_batch_size: 4
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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: 10
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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