--- language: - en license: apache-2.0 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: bert-base-uncased-rte results: - task: type: text-classification name: Text Classification dataset: name: GLUE RTE type: glue args: rte metrics: - type: accuracy value: 0.6895306859205776 name: Accuracy - task: type: natural-language-inference name: Natural Language Inference dataset: name: glue type: glue config: rte split: validation metrics: - type: accuracy value: 0.6823104693140795 name: Accuracy verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTc4OTUzYmQ0NWRkMjdmYjI3ZDhmNWU5MTQ1YTM4ZTQzOWM5MTJjYzlmMjM3ZTE2Y2ZhMGJlNTI0OTJhYjNmMCIsInZlcnNpb24iOjF9.siPkmQhZKOZ1k_SyS1xIMavpK_CQ8tHTm39McCIEjiF7G1x62lbuKfrZsLoKoPf9XpNJqXoaXIRPCpHBKlfwCA - type: precision value: 0.7047619047619048 name: Precision verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzdmMjk0ZjRkNzM4ZWE1ZGUyOWUxZTFjNmEyNTRmNjZmMDUxOTJlZmUxNjUzMWFhZTYzZTM1ZGNkMDg1YTMzYyIsInZlcnNpb24iOjF9.Cm2kMSTsWVPU9mBv8xAyvo7msTHdG3SECIYZ4kQ5RpN4NV3WE1k0EqmcGzAedwYNfSEg1qXL-qWDKOeoXDAnCw - type: recall value: 0.5648854961832062 name: Recall verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjc1NTMzYWI5OGRjODdhYmJjZDQ3ODdiMWE3ODYzZjNhZDg1MGIyNjA1YzQwNzcwYTQzNjJkNGVjNmNjMWJmNSIsInZlcnNpb24iOjF9.MwRAu1AKhCt__2vBjhvEqU0gvXaJ5EMOOotKmwGXsuF3eGJEEDDuiWBgu9y291aqndTTwWvuH9CNQjGKLCoNCw - type: auc value: 0.7394646031580048 name: AUC verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGQwMWVhZjlhNjhhZDRhNGYwNWUyOTZjMTgwMDQ5ZWM3MDcxNDc5OGJiNDE5NTNhOTU0MDMwYTdkYjcxNzFiZiIsInZlcnNpb24iOjF9.ZLyE_ZDWyVAr_GL_3lSqBmuIip7C13oj5kT1lI9JQOidt-IXsRHYUmJt_f7HWUNU1-FBD5lzHYcstF6WQ0VrAw - type: f1 value: 0.6271186440677967 name: F1 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmU0YjI4Y2MyMzU5ZTYzMmE0YzhjOTgwM2UwYTNhZDFmZWE3NTdhODMzYmU1ZWUxYTc2Yjk3Nzg3MjAyOThiOSIsInZlcnNpb24iOjF9.GJhnKNSHN5Sv9W3gl8fgPAAbM5EtMlhOHoOFcj_O65FLtcTi_ANpyv7gi41fPbMjS2TG4fgdVHQ_UZg7M6W2Cw - type: loss value: 0.7001310586929321 name: loss verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjMwMTY5OGVkMzVhMzdjMmY1YmIzYTViOTRlNzcxMTI4NWNiOTQ5ZjMwMjRlODE4ZWUwMGVhZjhiMmIzM2ViOSIsInZlcnNpb24iOjF9.IsJhfeeqnVZFn10sOkCW7vAzfw1WQMwR8b99B3-hct_lrI1xodt5ySGltDvx2Q8ufD6hzfQ7YaDeHytDmeeFBw --- # bert-base-uncased-rte This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE RTE dataset. It achieves the following results on the evaluation set: - Loss: 0.6972 - Accuracy: 0.6895 ## 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: 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 156 | 0.6537 | 0.6318 | | No log | 2.0 | 312 | 0.6383 | 0.6534 | | No log | 3.0 | 468 | 0.6972 | 0.6895 | ### Framework versions - Transformers 4.20.0.dev0 - Pytorch 1.11.0+cu113 - Datasets 2.1.0 - Tokenizers 0.12.1