README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: albert-base-v2-finetuned-qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9112209408749771

albert-base-v2-finetuned-qnli

This model is a fine-tuned version of albert-base-v2 on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.3194
• Accuracy: 0.9112

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3116	1.0	6547	0.2818	0.8849
0.2467	2.0	13094	0.2532	0.9001
0.1858	3.0	19641	0.3194	0.9112
0.1449	4.0	26188	0.4338	0.9103
0.0584	5.0	32735	0.5752	0.9052

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.18.0
• Tokenizers 0.10.3