metadata

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-mnli-100
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tmnam20/VieGLUE/MNLI
          type: tmnam20/VieGLUE
          config: mnli
          split: validation_matched
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.806346623270952

bert-base-multilingual-cased-mnli-100

This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/MNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.5343
Accuracy: 0.8063

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: 100
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
0.62	0.41	5000	0.6193	0.7459
0.5923	0.81	10000	0.5911	0.7610
0.5136	1.22	15000	0.5670	0.7808
0.4927	1.63	20000	0.5558	0.7852
0.4425	2.04	25000	0.5809	0.7844
0.4301	2.44	30000	0.5546	0.7940
0.4017	2.85	35000	0.5565	0.7963

Framework versions

Transformers 4.36.0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0