README.md

metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: mnlilearn
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9175142392188771

mnlilearn

This model is a fine-tuned version of microsoft/deberta-v3-large on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

• Loss: 0.4103
• Accuracy: 0.9175

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: 6e-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3631	1.0	49088	0.3129	0.9130
0.2267	2.0	98176	0.4157	0.9153

Framework versions

• Transformers 4.13.0.dev0
• Pytorch 1.10.0
• Datasets 1.15.2.dev0
• Tokenizers 0.10.3