metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-uncased
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: 0.9488
- Accuracy: {'accuracy': 0.889}
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.3898 | {'accuracy': 0.888} |
| No log | 2.0 | 250 | 0.5789 | {'accuracy': 0.865} |
| No log | 3.0 | 375 | 0.5372 | {'accuracy': 0.889} |
| 0.1772 | 4.0 | 500 | 0.6432 | {'accuracy': 0.891} |
| 0.1772 | 5.0 | 625 | 0.8819 | {'accuracy': 0.889} |
| 0.1772 | 6.0 | 750 | 0.9567 | {'accuracy': 0.883} |
| 0.1772 | 7.0 | 875 | 0.9547 | {'accuracy': 0.891} |
| 0.0207 | 8.0 | 1000 | 0.9466 | {'accuracy': 0.895} |
| 0.0207 | 9.0 | 1125 | 0.9615 | {'accuracy': 0.892} |
| 0.0207 | 10.0 | 1250 | 0.9488 | {'accuracy': 0.889} |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1