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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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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: xlm-roberta-ner-ja-v5 |
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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-ner-ja-v5 |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0556 |
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- Precision: 0.9131 |
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- Recall: 0.9879 |
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- F1-score: 0.9490 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:| |
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| 0.0888 | 1.0 | 837 | 0.0424 | 0.9014 | 0.9697 | 0.9343 | |
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| 0.0438 | 2.0 | 1674 | 0.0428 | 0.8647 | 0.9851 | 0.9210 | |
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| 0.0293 | 3.0 | 2511 | 0.0467 | 0.8746 | 0.9713 | 0.9205 | |
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| 0.0185 | 4.0 | 3348 | 0.0484 | 0.8707 | 0.9758 | 0.9203 | |
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| 0.0117 | 5.0 | 4185 | 0.0556 | 0.9131 | 0.9879 | 0.9490 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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