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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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