bert-sliding-window-9x_epoch_2

bert-sliding-window-9x_epoch_2

Model description

This is a fine-tuned version of DistilBERT for question answering tasks. The model was trained on SQuAD dataset.

Training procedure

The model was trained with the following hyperparameters:

• Learning Rate: 1e-05
• Batch Size: 32
• Epochs: 10
• Weight Decay: 0.01

Intended uses & limitations

This model is intended to be used for question answering tasks, particularly on SQuAD-like datasets. It performs best on factual questions where the answer can be found as a span of text within the given context.

Training Details

Training Data

The model was trained on the SQuAD dataset, which consists of questions posed by crowdworkers on a set of Wikipedia articles.

Training Hyperparameters

The model was trained with the following hyperparameters:

• learning_rate: 1e-05
• batch_size: 32
• num_epochs: 10
• weight_decay: 0.01

Uses

This model can be used for:

• Extracting answers from text passages given questions
• Question answering tasks
• Reading comprehension tasks

Limitations

• The model can only extract answers that are directly present in the given context
• Performance may vary on out-of-domain texts
• The model may struggle with complex reasoning questions

Additional Information

• Model type: DistilBERT
• Language: English
• License: MIT
• Framework: PyTorch