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# xlm-roberta-ner-ja

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1301
- F1: 0.8804

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 1451 | 0.1113          | 0.8286 |
| No log        | 2.0   | 2902 | 0.0990          | 0.8487 |
| No log        | 3.0   | 4353 | 0.1079          | 0.8611 |
| No log        | 4.0   | 5804 | 0.1120          | 0.8738 |
| No log        | 5.0   | 7255 | 0.1301          | 0.8804 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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transformers safetensors xlm-roberta token-classification ner ja base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us