bert-base-uncased-finetuned-QnA-v1

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.7610

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	39	3.3668
No log	2.0	78	3.2134
No log	3.0	117	3.1685
No log	4.0	156	3.1042
No log	5.0	195	3.1136
No log	6.0	234	2.9051
No log	7.0	273	2.9077
No log	8.0	312	2.9774
No log	9.0	351	2.9321
No log	10.0	390	2.9501
No log	11.0	429	2.8544
No log	12.0	468	2.8761
3.0255	13.0	507	2.8152
3.0255	14.0	546	2.8046
3.0255	15.0	585	2.6979
3.0255	16.0	624	2.6379
3.0255	17.0	663	2.7091
3.0255	18.0	702	2.6914
3.0255	19.0	741	2.7403
3.0255	20.0	780	2.7479

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.0+cu111
• Datasets 1.14.0
• Tokenizers 0.10.3