distilbert-base-uncased-finetuned-sqaud

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: 0.2831

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	14	0.9851
No log	2.0	28	0.6955
No log	3.0	42	0.5781
No log	4.0	56	0.4548
No log	5.0	70	0.4208
No log	6.0	84	0.3592
No log	7.0	98	0.3422
No log	8.0	112	0.3424
No log	9.0	126	0.4046
No log	10.0	140	0.3142
No log	11.0	154	0.3262
No log	12.0	168	0.2879
No log	13.0	182	0.3376
No log	14.0	196	0.2870
No log	15.0	210	0.2984
No log	16.0	224	0.2807
No log	17.0	238	0.2889
No log	18.0	252	0.2877
No log	19.0	266	0.2820
No log	20.0	280	0.2831

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.7.1
• Tokenizers 0.13.2