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library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ai-browsing-categories-text
results: []
---
<!-- 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-browsing-categories-text
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0274
- Accuracy: 0.9924
- F1: 0.9677
- Precision: 0.9737
- Recall: 0.9617
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1732 | 1.0 | 532 | 0.0586 | 0.9835 | 0.9274 | 0.9631 | 0.8943 |
| 0.0447 | 2.0 | 1064 | 0.0371 | 0.9884 | 0.9500 | 0.9681 | 0.9326 |
| 0.0272 | 3.0 | 1596 | 0.0319 | 0.9903 | 0.9583 | 0.9729 | 0.9442 |
| 0.0192 | 4.0 | 2128 | 0.0297 | 0.9907 | 0.9603 | 0.9714 | 0.9493 |
| 0.015 | 5.0 | 2660 | 0.0283 | 0.9917 | 0.9646 | 0.9736 | 0.9557 |
| 0.0115 | 6.0 | 3192 | 0.0284 | 0.9921 | 0.9662 | 0.9752 | 0.9573 |
| 0.0099 | 7.0 | 3724 | 0.0274 | 0.9927 | 0.9689 | 0.9761 | 0.9617 |
| 0.0079 | 8.0 | 4256 | 0.0274 | 0.9924 | 0.9677 | 0.9737 | 0.9617 |
### Framework versions
- Transformers 4.53.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4-dev.0
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