--- license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: autoevaluate-binary-classification results: - task: type: text-classification name: Text Classification dataset: name: glue type: glue args: sst2 metrics: - type: accuracy value: 0.8967889908256881 name: Accuracy - task: type: text-classification name: Text Classification dataset: name: glue type: glue config: sst2 split: validation metrics: - type: accuracy value: 0.8967889908256881 name: Accuracy verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTZmNGE1N2FjODM3OGJiM2Q2NTY5MzZjNGFhNGVjYzcwOTlkMzVhYjdmOTgwY2Y1NzMyZjY0NzAxMzZkMjM4NyIsInZlcnNpb24iOjF9.LabPe-QWLUUJdPyQ0Ki9rHq74opfAO1fxvu2FjUFiY9zhxAe0RKNjZRHPbrF10249Z3kDZSAq2yzQ1TjKvoLBQ - type: precision value: 0.8898678414096917 name: Precision verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTczZjUwY2MzNTMzY2VlMjFmZGI2MzAwNTEwM2IzYWVkYmFiNjk0MDM3YmYzYjFmNGM3NWI5NDIzODJjMTA1ZCIsInZlcnNpb24iOjF9.3RC343Rtep7yxGH82c1WV2IAVqhJTRoOwiwFVp_w0K0JK_dTqnfEylLb1yMt367ztvkhhOgRn4i9GsL4ZNC5BQ - type: recall value: 0.9099099099099099 name: Recall verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM4M2Y3YTVjOTlhZjc2OGUxMzFhNGI3YzM4MDI0NDMwMmQyMmRmY2MyMTI5ZTdmYWVjMTlmYWE0N2Q0ZjJiNyIsInZlcnNpb24iOjF9.lMKosw258_E40HdqY8BFyWVJYAMx4cpVyYusGEqN429_cv3DzeIMaOr00trGsJX3BIqr-j5ScjLVV79f5nK2CA - type: auc value: 0.9672186789593331 name: AUC verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzY1YmM4YjJhNTY2ZmIyYmI5ZTBjZjc3MDZiMzQ3ZTEyZWQ1M2I4ZTk4OGYwNzZiY2VlODRkODRjNTg2MDNmMSIsInZlcnNpb24iOjF9.tO3GQ5Rgl26zHz18-yR2wtcajmb_MEPNCZiA1Exz4255-m1iDFyMPM2Pw4s75xUSXWzsF--bo6eqmCLo4yjkBw - type: f1 value: 0.8997772828507795 name: F1 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmM0ZjhjZWY2ZGZiYWZhOTY2OWUwNzcxMTRlNjU4MDMyMWViMjg2YzE0YzBiMzVlYTU2ODkyZWY0MzcxOWJlOCIsInZlcnNpb24iOjF9.sySuyn4j72Gt3wstru118StL7pzGgZKzAPtE0FM7HVfdBrVXwZckKaUmoQR-nKaVynbo1h4mykNdM-_MwmLlCA - type: loss value: 0.30092036724090576 name: loss verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDQ2ZjJiMjVhNTMxZGIxMTFlMjVhYTQyOGI2YjgyOTI3OTQ4NGU0ZWYxMDY2MmI1OGNiNDcwNTU3MmEzM2YzZSIsInZlcnNpb24iOjF9.MGCrOvwyOdMQ91z2pzgsIxS-PMCZy2YwNX7IuMNAVokRhTSGUYtFt-8px1Dv9w39IT6ZbySZ7kQQKz6kK8HWAQ - type: matthews_correlation value: 0.793630584795814 name: matthews_correlation verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGY5ODMyZjc4MTk0NWU1YTRmNGI5NDU0ZGRlMDEwY2ZhN2YzMjAxNDE2MTY4ZTI2OWZjMzkwMzc5NTY3NTlkMSIsInZlcnNpb24iOjF9.1WB_1AIkuk68pphfqpqB_T1VpM3wJPe7mNGOvaDANcek7TKUFuT6kA8J1h1SICS_80mdXDI4yJGGZy3CZwpXDQ --- # binary-classification This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.3009 - Accuracy: 0.8968 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.175 | 1.0 | 4210 | 0.3009 | 0.8968 | ### Framework versions - Transformers 4.19.2 - Pytorch 1.11.0+cu113 - Datasets 2.2.2 - Tokenizers 0.12.1