Model description

Finetuned on SQUAD2.0 Dataset

F1: 83.738696142672

Trained on single V100 GPU

Everyone is welcome to use~

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Performance

• HasAns_exact': 77.1255060728745, 'HasAns_f1': 83.87812741260885, 'HasAns_total': 5928,

• 'NoAns_exact': 83.59966358284272, 'NoAns_f1': 83.59966358284272, 'NoAns_total': 5945,

• 'best_exact': 80.36721974227238, 'best_exact_thresh': 0.0,

• 'best_f1': 83.7386961426719, 'best_f1_thresh': 0.0,

• 'exact': 80.36721974227238,

• 'f1': 83.738696142672,

• 'total': 11873

roberta-base-finetuned-squad2-lwt

This model is a fine-tuned version of roberta-base on the squad_v2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.9441

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.871	1.0	8239	0.8156
0.6787	2.0	16478	0.8494
0.4867	3.0	24717	0.9441

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6