metadata

language:
  - en
base_model: google-t5/t5-base
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: QNLI
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9282445542742083

QNLI

This model is a fine-tuned version of google-t5/t5-base on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.2215
Accuracy: 0.9282

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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2856	1.0	1637	0.2216	0.9149
0.2258	2.0	3274	0.2060	0.9220
0.1791	3.0	4911	0.2038	0.9277
0.1476	4.0	6548	0.2215	0.9282
0.1263	5.0	8185	0.2301	0.9279

Framework versions

Transformers 4.43.3
Pytorch 1.11.0+cu113
Datasets 2.20.0
Tokenizers 0.19.1