|
---
|
|
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: []
|
|
---
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# distilbert-base-uncased-lora-text-classification |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2701 |
|
- Accuracy: {'accuracy': 0.867} |
|
|
|
## 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 | 0.4135 | {'accuracy': 0.854} | |
|
| 0.4732 | 2.0 | 500 | 0.5962 | {'accuracy': 0.846} | |
|
| 0.4732 | 3.0 | 750 | 0.6645 | {'accuracy': 0.869} | |
|
| 0.3296 | 4.0 | 1000 | 0.8788 | {'accuracy': 0.86} | |
|
| 0.3296 | 5.0 | 1250 | 0.9247 | {'accuracy': 0.858} | |
|
| 0.1992 | 6.0 | 1500 | 0.9763 | {'accuracy': 0.871} | |
|
| 0.1992 | 7.0 | 1750 | 1.1154 | {'accuracy': 0.866} | |
|
| 0.0876 | 8.0 | 2000 | 1.2105 | {'accuracy': 0.87} | |
|
| 0.0876 | 9.0 | 2250 | 1.2144 | {'accuracy': 0.871} | |
|
| 0.0436 | 10.0 | 2500 | 1.2701 | {'accuracy': 0.867} | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cpu |
|
- Datasets 2.16.0 |
|
- Tokenizers 0.19.1 |
