--- license: apache-2.0 base_model: bert-base-cased tags: - generated_from_keras_callback model-index: - name: ukzash1/bert_fineTuned results: - task: type: sequence-classification dataset: name: glue type: cola metrics: - name: Validation Accuracy type: Accuracy value: 0.8207 source: name: Hugging Face Model Hub url: https://huggingface.co/ukzash1/bert_fineTuned widget: - text: I liked this movie output: - label: Acceptable score: 0.8 - label: Not Acceptable score: 0.2 - text: This not is bad output: - label: Acceptable score: 0.2 - label: Not Acceptable score: 0.8 library_name: transformers language: - en metrics: - accuracy pipeline_tag: text-classification --- # ukzash1/bert_fineTuned This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.3426 - Train Accuracy: 0.8555 - Validation Loss: 0.4083 - Validation Accuracy: 0.8198 - Epoch: 1 ## 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: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| | 0.5409 | 0.7317 | 0.5398 | 0.7756 | 0 | | 0.3426 | 0.8555 | 0.4083 | 0.8198 | 1 | ### Framework versions - Transformers 4.38.2 - TensorFlow 2.13.0 - Datasets 2.20.0 - Tokenizers 0.15.2