m_distilbert_large_qa_model

This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on the subjqa dataset. It achieves the following results on the evaluation set:

• Loss: 2.9942

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

Training Loss	Epoch	Step	Validation Loss
No log	1.0	32	2.7813
No log	2.0	64	2.7317
No log	3.0	96	2.8938
No log	4.0	128	2.9347
No log	5.0	160	2.9942

Framework versions

• Transformers 4.27.3
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2