metadata

language:
  - en
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
  - generated_from_trainer
datasets:
  - tmnam20/VieGLUE
metrics:
  - accuracy
model-index:
  - name: mdeberta-v3-base-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: 0.8412327095199349

mdeberta-v3-base-mnli-100

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tmnam20/VieGLUE/MNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.4764
Accuracy: 0.8412

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
0.5194	0.41	5000	0.4901	0.8127
0.4861	0.81	10000	0.4713	0.8114
0.3993	1.22	15000	0.4508	0.8285
0.3867	1.63	20000	0.4546	0.8302
0.3496	2.04	25000	0.4765	0.8295
0.3376	2.44	30000	0.4828	0.8315
0.3104	2.85	35000	0.4852	0.8314

Framework versions

Transformers 4.35.2
Pytorch 2.2.0.dev20231203+cu121
Datasets 2.15.0
Tokenizers 0.15.0