metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - super_glue
model-index:
  - name: qna2_deberta_model
    results: []

boolq_deberta_model

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

eval_loss: 0.4066
eval_accuracy: 0.8468
eval_runtime: 111.0255
eval_samples_per_second: 29.453
eval_steps_per_second: 1.846
epoch: 2.0
step: 1180

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

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2