squeezebert-mnli-headless-finetuned-mrpc

This model is a fine-tuned version of squeezebert/squeezebert-mnli-headless on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.3142
• Accuracy: 0.8824
• F1: 0.9137

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: 32
• eval_batch_size: 32
• seed: 73
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	115	0.4461	0.8162	0.8705
No log	2.0	230	0.3844	0.8407	0.8866
No log	3.0	345	0.3181	0.8848	0.9156
No log	4.0	460	0.3159	0.8775	0.9091
0.3723	5.0	575	0.3142	0.8824	0.9137

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3