m_bert_large_qa_model_1

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m_bert_large_qa_model_1

This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the subjqa dataset. It achieves the following results on the evaluation set:

• Loss: 5.9072

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: 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: 5

Training results

Framework versions

• Transformers 4.28.0
• Pytorch 1.13.0a0+d321be6
• Datasets 2.12.0
• Tokenizers 0.13.3