---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- msra_ner
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-msra
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xlm-roberta-base-finetuned-msra

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the msra_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0661
- F1: 0.8221

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1946        | 1.0   | 938  | 0.0948          | 0.6865 |
| 0.0744        | 2.0   | 1876 | 0.0813          | 0.7592 |
| 0.0466        | 3.0   | 2814 | 0.0697          | 0.7956 |
| 0.0307        | 4.0   | 3752 | 0.0655          | 0.8104 |
| 0.0219        | 5.0   | 4690 | 0.0661          | 0.8221 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1