hackMIT-finetuned-sst2

This model is a fine-tuned version of Blaine-Mason/hackMIT-finetuned-sst2 on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 1.0046
• Accuracy: 0.7970

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: 1.7339491016138283e-05
• train_batch_size: 64
• eval_batch_size: 16
• seed: 23
• 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
0.0652	1.0	1053	0.9837	0.7970
0.0586	2.0	2106	0.9927	0.7959
0.0549	3.0	3159	1.0046	0.7970

Framework versions

• Transformers 4.9.2
• Pytorch 1.9.0+cu102
• Datasets 1.11.0
• Tokenizers 0.10.3