README.md

metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - text-classification
metrics:
  - accuracy
model-index:
  - name: ft-bert-with-swag
    results:
      - task:
          name: Multiple Choice
          type: multiple-choice
        dataset:
          name: swag
          type: text-classification
          config: regular
          split: train[:500]
          args: regular
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.48

ft-bert-with-swag

This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:

• Loss: 1.2843
• Accuracy: 0.48

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	13	1.2843	0.48

Framework versions

• Transformers 4.35.2
• Pytorch 2.0.0
• Datasets 2.15.0
• Tokenizers 0.15.0