README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - super_glue
metrics:
  - accuracy
model-index:
  - name: finetune_deberta_small_model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: super_glue
          type: super_glue
          config: boolq
          split: train
          args: boolq
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8021406727828746

finetune_deberta_small_model

This model is a fine-tuned version of nc33/finetune_deberta_small_model on the super_glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.6788
• Accuracy: 0.8021

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3666	1.0	590	0.5625	0.8003
0.2501	2.0	1180	0.6762	0.7976
0.2343	3.0	1770	0.6788	0.8021

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2