m_bert_large_qa_model_2

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: 4.3531

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	64	2.6049
No log	2.0	128	2.8487
No log	3.0	192	3.4915
No log	4.0	256	4.0808
No log	5.0	320	4.3531

Framework versions

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