metadata
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: []
library_name: peft
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: 1.0049
- Accuracy: {'accuracy': 0.883}
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 | 0.3972 | {'accuracy': 0.858} |
| 0.4079 | 2.0 | 500 | 0.4154 | {'accuracy': 0.878} |
| 0.4079 | 3.0 | 750 | 0.6355 | {'accuracy': 0.87} |
| 0.1558 | 4.0 | 1000 | 0.7310 | {'accuracy': 0.876} |
| 0.1558 | 5.0 | 1250 | 0.8508 | {'accuracy': 0.877} |
| 0.0432 | 6.0 | 1500 | 0.9112 | {'accuracy': 0.876} |
| 0.0432 | 7.0 | 1750 | 1.0137 | {'accuracy': 0.873} |
| 0.0208 | 8.0 | 2000 | 0.9952 | {'accuracy': 0.88} |
| 0.0208 | 9.0 | 2250 | 0.9904 | {'accuracy': 0.881} |
| 0.0035 | 10.0 | 2500 | 1.0049 | {'accuracy': 0.883} |
Framework versions
- PEFT 0.5.0
- Transformers 4.32.1
- Pytorch 2.1.0.dev20230905
- Datasets 2.14.4
- Tokenizers 0.13.3