| | --- |
| | 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 an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.9731 |
| | - Accuracy: {'accuracy': 0.891} |
| |
|
| | ## 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 | 0.3222 | {'accuracy': 0.895} | |
| | | 0.4357 | 2.0 | 500 | 0.4879 | {'accuracy': 0.872} | |
| | | 0.4357 | 3.0 | 750 | 0.5919 | {'accuracy': 0.895} | |
| | | 0.1751 | 4.0 | 1000 | 0.7484 | {'accuracy': 0.885} | |
| | | 0.1751 | 5.0 | 1250 | 0.7662 | {'accuracy': 0.892} | |
| | | 0.0628 | 6.0 | 1500 | 0.8518 | {'accuracy': 0.88} | |
| | | 0.0628 | 7.0 | 1750 | 0.9047 | {'accuracy': 0.894} | |
| | | 0.0186 | 8.0 | 2000 | 0.9434 | {'accuracy': 0.894} | |
| | | 0.0186 | 9.0 | 2250 | 0.9598 | {'accuracy': 0.895} | |
| | | 0.0083 | 10.0 | 2500 | 0.9731 | {'accuracy': 0.891} | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.10.0 |
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
