metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-uncased
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 the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2300
- Accuracy: {'accuracy': 0.861}
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: 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 | 250 | 0.5358 | {'accuracy': 0.853} |
| 0.398 | 2.0 | 500 | 0.5237 | {'accuracy': 0.866} |
| 0.398 | 3.0 | 750 | 0.6152 | {'accuracy': 0.849} |
| 0.1864 | 4.0 | 1000 | 0.7506 | {'accuracy': 0.855} |
| 0.1864 | 5.0 | 1250 | 0.9820 | {'accuracy': 0.867} |
| 0.0382 | 6.0 | 1500 | 1.0581 | {'accuracy': 0.856} |
| 0.0382 | 7.0 | 1750 | 1.1583 | {'accuracy': 0.862} |
| 0.0149 | 8.0 | 2000 | 1.2200 | {'accuracy': 0.858} |
| 0.0149 | 9.0 | 2250 | 1.2581 | {'accuracy': 0.862} |
| 0.006 | 10.0 | 2500 | 1.2300 | {'accuracy': 0.861} |
Framework versions
- PEFT 0.8.1
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1