metadata
library_name: peft
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-lora-text-classification
results: []
distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9980
- Accuracy: {'accuracy': 0.884}
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3876 | {'accuracy': 0.88} |
| 0.452 | 2.0 | 500 | 0.4465 | {'accuracy': 0.864} |
| 0.452 | 3.0 | 750 | 0.4792 | {'accuracy': 0.882} |
| 0.2137 | 4.0 | 1000 | 0.7374 | {'accuracy': 0.883} |
| 0.2137 | 5.0 | 1250 | 0.8041 | {'accuracy': 0.886} |
| 0.0584 | 6.0 | 1500 | 0.8809 | {'accuracy': 0.89} |
| 0.0584 | 7.0 | 1750 | 0.8800 | {'accuracy': 0.887} |
| 0.0275 | 8.0 | 2000 | 0.9635 | {'accuracy': 0.885} |
| 0.0275 | 9.0 | 2250 | 1.0078 | {'accuracy': 0.882} |
| 0.0142 | 10.0 | 2500 | 0.9980 | {'accuracy': 0.884} |
Framework versions
- PEFT 0.15.1
- Transformers 4.47.1
- Pytorch 2.5.1+cpu
- Datasets 3.5.0
- Tokenizers 0.21.0