README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: xlnet-base-mnli-finetuned
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9118695873662761

xlnet-base-mnli-finetuned

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: 0.3456
• Accuracy: 0.9119

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.336	1.0	49087	0.3299	0.9010
0.2582	2.0	98174	0.3456	0.9119

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1