| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - 0.0.2 |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: ai-categories-text |
| results: [] |
| datasets: |
| - tinutmap/ai-categories-data |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ai-categories-text |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an tinutmap/ai-categories-data 's `train` dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0037 |
| - Accuracy: 0.9991 |
| - F1: 0.9926 |
| - Precision: 0.9926 |
| - Recall: 0.9926 |
|
|
| ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.1646 | 1.0 | 599 | 0.0271 | 0.9956 | 0.9620 | 0.9834 | 0.9415 | |
| | 0.0219 | 2.0 | 1198 | 0.0093 | 0.9984 | 0.9862 | 0.9887 | 0.9838 | |
| | 0.0093 | 3.0 | 1797 | 0.0062 | 0.9989 | 0.9907 | 0.9905 | 0.9908 | |
| | 0.0054 | 4.0 | 2396 | 0.0048 | 0.9991 | 0.9924 | 0.9919 | 0.9929 | |
| | 0.0034 | 5.0 | 2995 | 0.0043 | 0.9991 | 0.9928 | 0.9912 | 0.9944 | |
| | 0.0021 | 6.0 | 3594 | 0.0038 | 0.9992 | 0.9931 | 0.9923 | 0.9940 | |
| | 0.0017 | 7.0 | 4193 | 0.0038 | 0.9991 | 0.9928 | 0.9933 | 0.9922 | |
| | 0.0015 | 8.0 | 4792 | 0.0037 | 0.9991 | 0.9926 | 0.9926 | 0.9926 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.52.2 |
| - Pytorch 2.7.0+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
