fnet-large-finetuned-rte

This model is a fine-tuned version of google/fnet-large on the GLUE RTE dataset. It achieves the following results on the evaluation set:

• Loss: 0.7528
• Accuracy: 0.6426

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: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7105	1.0	623	0.6887	0.5740
0.6714	2.0	1246	0.6742	0.6209
0.509	3.0	1869	0.7528	0.6426

Framework versions

• Transformers 4.11.0.dev0
• Pytorch 1.9.0
• Datasets 1.12.1
• Tokenizers 0.10.3