README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - circa
metrics:
  - accuracy
model-index:
  - name: BERT_QandA
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: circa
          type: circa
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8764964388543719

BERT_QandA

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

• Loss: 0.4298
• Accuracy: 0.8765

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: 3e-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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5797	1.0	619	0.4172	0.8532
0.3531	2.0	1238	0.3885	0.8735
0.2334	3.0	1857	0.4298	0.8765

Framework versions

• Transformers 4.26.1
• Pytorch 2.0.0.dev20230220
• Datasets 2.10.0
• Tokenizers 0.11.0