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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
model-index:
- name: bert-base-multilingual-cased-sst2-1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tmnam20/VieGLUE/SST2
type: tmnam20/VieGLUE
config: sst2
split: validation
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.8841743119266054
---
<!-- 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-sst2-1
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the tmnam20/VieGLUE/SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4333
- Accuracy: 0.8842
## 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: 1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3821 | 0.24 | 500 | 0.3799 | 0.8314 |
| 0.3198 | 0.48 | 1000 | 0.4079 | 0.8417 |
| 0.272 | 0.71 | 1500 | 0.3721 | 0.8670 |
| 0.2847 | 0.95 | 2000 | 0.3885 | 0.8567 |
| 0.1893 | 1.19 | 2500 | 0.4329 | 0.8589 |
| 0.2124 | 1.43 | 3000 | 0.4133 | 0.8532 |
| 0.2208 | 1.66 | 3500 | 0.3665 | 0.8773 |
| 0.2219 | 1.9 | 4000 | 0.4164 | 0.8601 |
| 0.1562 | 2.14 | 4500 | 0.4350 | 0.8635 |
| 0.1399 | 2.38 | 5000 | 0.4571 | 0.8761 |
| 0.1399 | 2.61 | 5500 | 0.4346 | 0.8796 |
| 0.1403 | 2.85 | 6000 | 0.4325 | 0.8819 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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