README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: xlnet-base-cased-finetuned-wnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: wnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5633802816901409

xlnet-base-cased-finetuned-wnli

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

• Loss: 0.6874
• Accuracy: 0.5634

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
No log	1.0	40	0.7209	0.5352
No log	2.0	80	0.6874	0.5634
No log	3.0	120	0.6908	0.5634
No log	4.0	160	0.6987	0.4930
No log	5.0	200	0.6952	0.5634

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3