transformers safetensors xlm-roberta multiple-choice generated_from_trainer base_model:xlm-roberta-large license:mit endpoints_compatible region:us
---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wvs-chn-finetuned
  results: []
---

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

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4045
- Accuracy: 0.4952

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 5
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5206        | 1.0   | 42   | 1.5011          | 0.3381   |
| 1.5051        | 2.0   | 84   | 1.4779          | 0.4381   |
| 1.5174        | 3.0   | 126  | 1.4951          | 0.3429   |
| 1.5292        | 4.0   | 168  | 1.4328          | 0.5381   |
| 1.4917        | 5.0   | 210  | 1.4045          | 0.4952   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
