CodeSolutionsDev/question-detection-default-20260119

1---2library_name: transformers3license: apache-2.04base_model: distilbert/distilbert-base-uncased5tags:6- generated_from_trainer7metrics:8- accuracy9- f110model-index:11- name: question-detection-default-2026011912  results: []13---14 15<!-- This model card has been generated automatically according to the information the Trainer had access to. You16should probably proofread and complete it, then remove this comment. -->17 18# question-detection-default-2026011919 20This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.21It achieves the following results on the evaluation set:22- Loss: 0.196823- Accuracy: 0.966424- F1: 0.966425 26## Model description27 28More information needed29 30## Intended uses & limitations31 32More information needed33 34## Training and evaluation data35 36More information needed37 38## Training procedure39 40### Training hyperparameters41 42The following hyperparameters were used during training:43- learning_rate: 5e-0544- train_batch_size: 845- eval_batch_size: 846- seed: 4247- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments48- lr_scheduler_type: linear49- num_epochs: 650- mixed_precision_training: Native AMP51 52### Training results53 54| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |55|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|56| 0.4984        | 1.0   | 75   | 0.1219          | 0.9530   | 0.9530 |57| 0.1356        | 2.0   | 150  | 0.1585          | 0.9530   | 0.9530 |58| 0.0589        | 3.0   | 225  | 0.1968          | 0.9664   | 0.9664 |59| 0.0006        | 4.0   | 300  | 0.1901          | 0.9664   | 0.9664 |60| 0.0006        | 5.0   | 375  | 0.1904          | 0.9664   | 0.9664 |61| 0.0005        | 6.0   | 450  | 0.1921          | 0.9664   | 0.9664 |62 63 64### Framework versions65 66- Transformers 4.57.367- Pytorch 2.9.0+cu12668- Datasets 4.0.069- Tokenizers 0.22.270