---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: jim-crow-test2323
  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-test2323

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: 0.0984
- Accuracy: 0.9720
- Precision: 0.9340
- Recall: 0.9706
- F1: 0.9519
- Macro Precision: 0.9610
- Macro Recall: 0.9716
- Macro F1: 0.9661
- Tn: 248
- Fp: 7
- Fn: 3
- Tp: 99

## 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: 32
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Macro Precision | Macro Recall | Macro F1 | Tn  | Fp | Fn | Tp  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:---------------:|:------------:|:--------:|:---:|:--:|:--:|:---:|
| 0.0677        | 1.0   | 90   | 0.1643          | 0.9524   | 0.8899    | 0.9510 | 0.9194 | 0.9349          | 0.9520       | 0.9428   | 243 | 12 | 5  | 97  |
| 0.1282        | 2.0   | 180  | 0.0984          | 0.9720   | 0.9340    | 0.9706 | 0.9519 | 0.9610          | 0.9716       | 0.9661   | 248 | 7  | 3  | 99  |
| 0.0683        | 3.0   | 270  | 0.1819          | 0.9720   | 0.9694    | 0.9314 | 0.95   | 0.9712          | 0.9598       | 0.9653   | 252 | 3  | 7  | 95  |
| 0.0226        | 4.0   | 360  | 0.1095          | 0.9692   | 0.9174    | 0.9804 | 0.9479 | 0.9547          | 0.9725       | 0.9630   | 246 | 9  | 2  | 100 |
| 0.0219        | 5.0   | 450  | 0.1491          | 0.9720   | 0.9423    | 0.9608 | 0.9515 | 0.9632          | 0.9686       | 0.9659   | 249 | 6  | 4  | 98  |


### Framework versions

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