---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cipher-detective-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cipher-detective-classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2801
- Accuracy: 0.6127
- Macro Precision: 0.6196
- Macro Recall: 0.6392
- Macro F1: 0.6217

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: cosine
- lr_scheduler_warmup_steps: 0.06
- num_epochs: 5.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro Recall | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
| 3.6387        | 1.0   | 912  | 1.7823          | 0.4904   | 0.5276          | 0.5280       | 0.5108   |
| 3.0345        | 2.0   | 1824 | 1.4479          | 0.5485   | 0.5757          | 0.5806       | 0.5552   |
| 2.7365        | 3.0   | 2736 | 1.3711          | 0.5835   | 0.6195          | 0.6139       | 0.5988   |
| 2.5225        | 4.0   | 3648 | 1.2933          | 0.6067   | 0.6196          | 0.6332       | 0.6186   |
| 2.6116        | 5.0   | 4560 | 1.2801          | 0.6127   | 0.6196          | 0.6392       | 0.6217   |


### Framework versions

- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2