--- language: - en license: apache-2.0 base_model: google/fnet-base tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation model-index: - name: fnet-base-finetuned-cola results: - task: name: Text Classification type: text-classification dataset: name: GLUE COLA type: glue args: cola metrics: - name: Matthews Correlation type: matthews_correlation value: 0.3934207280665654 --- # fnet-base-finetuned-cola This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the GLUE COLA dataset. It achieves the following results on the evaluation set: - Loss: 0.6476 - Matthews Correlation: 0.3934 ## 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: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.61 | 1.0 | 268 | 0.5818 | 0.1606 | | 0.5265 | 2.0 | 536 | 0.5489 | 0.3415 | | 0.4161 | 3.0 | 804 | 0.5454 | 0.3451 | | 0.3324 | 4.0 | 1072 | 0.5746 | 0.3869 | | 0.2657 | 5.0 | 1340 | 0.6476 | 0.3934 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 1.13.1 - Datasets 2.19.1 - Tokenizers 0.19.1