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---
language:
- en
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
datasets:
- tmnam20/VieGLUE
metrics:
- accuracy
- f1
model-index:
- name: bert-base-multilingual-cased-qqp-10
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tmnam20/VieGLUE/QQP
type: tmnam20/VieGLUE
config: qqp
split: validation
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8885975760573831
- name: F1
type: f1
value: 0.8473737716028464
---
<!-- 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. -->
# bert-base-multilingual-cased-qqp-10
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the tmnam20/VieGLUE/QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3064
- Accuracy: 0.8886
- F1: 0.8474
- Combined Score: 0.8680
## 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: 32
- eval_batch_size: 16
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3263 | 0.44 | 5000 | 0.3272 | 0.8557 | 0.8081 | 0.8319 |
| 0.3084 | 0.88 | 10000 | 0.2968 | 0.8680 | 0.8191 | 0.8436 |
| 0.2424 | 1.32 | 15000 | 0.2998 | 0.8768 | 0.8324 | 0.8546 |
| 0.2171 | 1.76 | 20000 | 0.2995 | 0.8847 | 0.8449 | 0.8648 |
| 0.1796 | 2.2 | 25000 | 0.3124 | 0.8857 | 0.8424 | 0.8640 |
| 0.1811 | 2.64 | 30000 | 0.2963 | 0.8883 | 0.8477 | 0.8680 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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