distilbert-base-uncased-finetuned-mathqa

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

• Loss: 1.5056
• Accuracy: 0.3445

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: 5e-05
• train_batch_size: 10
• eval_batch_size: 10
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.5584	1.0	2970	1.5429	0.3029
1.485	2.0	5940	1.4965	0.3328
1.3677	3.0	8910	1.5056	0.3445

Framework versions

• Transformers 4.40.1
• Pytorch 2.1.2
• Datasets 2.19.0
• Tokenizers 0.19.1