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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: 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
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