my_qa_model

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

• Loss: 0.5865

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: 0.0002
• 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: 15

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	96	0.6101
No log	2.0	192	0.3681
No log	3.0	288	0.3647
No log	4.0	384	0.3718
No log	5.0	480	0.3506
0.4973	6.0	576	0.3861
0.4973	7.0	672	0.4109
0.4973	8.0	768	0.5558
0.4973	9.0	864	0.5509
0.4973	10.0	960	0.4134
0.1005	11.0	1056	0.4974
0.1005	12.0	1152	0.5251
0.1005	13.0	1248	0.6089
0.1005	14.0	1344	0.5672
0.1005	15.0	1440	0.5865

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3