---
license: mit
tags:
- generated_from_trainer
model-index:
- name: XLM_R_Extractive_QA_Vi_En_Zh
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# XLM_R_Extractive_QA_Vi_En_Zh

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: 2.4547

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0082        | 1.0   | 3245 | 2.3766          |
| 1.681         | 2.0   | 6491 | 2.3099          |
| 1.4326        | 3.0   | 9735 | 2.4547          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3