---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
base_model: bert-base-multilingual-cased
model-index:
- name: xnli_m_bert_only_vi
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: xnli
      type: xnli
      config: vi
      split: train
      args: vi
    metrics:
    - type: accuracy
      value: 0.7401606425702811
      name: Accuracy
---

<!-- 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. -->

# xnli_m_bert_only_vi

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2539
- Accuracy: 0.7402

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6634        | 1.0   | 3068  | 0.7030          | 0.7016   |
| 0.5848        | 2.0   | 6136  | 0.6031          | 0.7518   |
| 0.5003        | 3.0   | 9204  | 0.6296          | 0.7418   |
| 0.4159        | 4.0   | 12272 | 0.6398          | 0.7482   |
| 0.3395        | 5.0   | 15340 | 0.7042          | 0.7438   |
| 0.2648        | 6.0   | 18408 | 0.9274          | 0.7345   |
| 0.2062        | 7.0   | 21476 | 0.9433          | 0.7373   |
| 0.1544        | 8.0   | 24544 | 1.0372          | 0.7378   |
| 0.1164        | 9.0   | 27612 | 1.1879          | 0.7357   |
| 0.0882        | 10.0  | 30680 | 1.2539          | 0.7402   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1