Glue_distilbert_new

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

• Loss: 0.6153
• Accuracy: 0.6397
• F1: 0.7361
• Combined Score: 0.6879

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: 1024
• eval_batch_size: 1024
• seed: 33
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6415	1.0	4	0.6363	0.6838	0.8122	0.7480
0.6292	2.0	8	0.6101	0.6838	0.8122	0.7480
0.6244	3.0	12	0.6047	0.6838	0.8122	0.7480
0.6075	4.0	16	0.6153	0.6397	0.7361	0.6879

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.8.0
• Tokenizers 0.11.6