---
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