metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: classifier
results: []
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: 0.0090
- Accuracy: 1.0
- F1 Macro: 1.0
- F1 Weighted: 1.0
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
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 1.2992 | 1.0 | 63 | 0.1976 | 1.0 | 1.0 | 1.0 |
| 0.1725 | 2.0 | 126 | 0.0234 | 1.0 | 1.0 | 1.0 |
| 0.0314 | 3.0 | 189 | 0.0133 | 1.0 | 1.0 | 1.0 |
| 0.0143 | 4.0 | 252 | 0.0101 | 1.0 | 1.0 | 1.0 |
| 0.0124 | 5.0 | 315 | 0.0093 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2