test_qa_model_1

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: 1.9251

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	250	2.2315
2.6452	2.0	500	1.5474
2.6452	3.0	750	1.4077
1.0097	4.0	1000	1.4167
1.0097	5.0	1250	1.5154
0.5496	6.0	1500	1.6048
0.5496	7.0	1750	1.7669
0.3364	8.0	2000	1.7872
0.3364	9.0	2250	1.9107
0.2434	10.0	2500	1.9251

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.2