---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: jim-crow-test
  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. -->

# jim-crow-test

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: 0.1308
- Accuracy: 0.9748
- F1: 0.9565
- Precision: 0.9429
- Recall: 0.9706

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0611        | 1.0   | 90   | 0.1527          | 0.9552   | 0.9245 | 0.8909    | 0.9608 |
| 0.0686        | 2.0   | 180  | 0.1356          | 0.9636   | 0.9378 | 0.9159    | 0.9608 |
| 0.0052        | 3.0   | 270  | 0.1308          | 0.9748   | 0.9565 | 0.9429    | 0.9706 |
| 0.0206        | 4.0   | 360  | 0.1425          | 0.9636   | 0.9372 | 0.9238    | 0.9510 |
| 0.0049        | 5.0   | 450  | 0.1565          | 0.9692   | 0.9458 | 0.9505    | 0.9412 |


### Framework versions

- Transformers 5.7.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2