metadata
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: []
cipher-detective-classifier
This model is a fine-tuned version of 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