bert-base-uncased-finetuned-copa-data-new

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

• Loss: 0.5995
• Accuracy: 0.7000

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: 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	25	0.6564	0.6600
No log	2.0	50	0.5995	0.7000

Framework versions

• Transformers 4.16.2
• Pytorch 1.10.0+cu111
• Datasets 1.18.3
• Tokenizers 0.11.0