runningsnake/bert-base-sequence-classification

1---2license: apache-2.03base_model: bert-base-uncased4tags:5- generated_from_keras_callback6model-index:7- name: runningsnake/bert-base-sequence-classification8  results: []9---10 11<!-- This model card has been generated automatically according to the information Keras had access to. You should12probably proofread and complete it, then remove this comment. -->13 14# runningsnake/bert-base-sequence-classification15 16This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.17It achieves the following results on the evaluation set:18- Train Loss: 0.082519- Train Accuracy: 0.976620- Validation Loss: 0.506421- Validation Accuracy: 0.843122- Epoch: 223 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## How to use33 34More information needed35 36## Limitations and bias37 38More information needed39 40## Training and evaluation data41 42More information needed43 44## Training procedure45 46### Training hyperparameters47 48The following hyperparameters were used during training:49- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1377, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}50- training_precision: float3251 52### Training results53 54| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |55|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|56| 0.2559     | 0.9057         | 0.5082          | 0.8211              | 0     |57| 0.1004     | 0.9673         | 0.5064          | 0.8431              | 1     |58| 0.0825     | 0.9766         | 0.5064          | 0.8431              | 2     |59 60 61### Framework versions62 63- Transformers 4.31.064- TensorFlow 2.12.065- Datasets 2.14.066- Tokenizers 0.13.367 68## Evaluation results69 70More information needed