m_albert_qa_model

This model is a fine-tuned version of albert-base-v2 on the subjqa dataset. It achieves the following results on the evaluation set:

• Loss: 2.8510

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	2.6117
No log	2.0	64	2.5636
No log	3.0	96	2.6828
No log	4.0	128	2.8268
No log	5.0	160	2.8510

Framework versions

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