| --- |
| library_name: peft |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - base_model:adapter:distilbert-base-uncased |
| - lora |
| - transformers |
| 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 IMDb dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9717 |
| - Accuracy: {'accuracy': 0.872} |
|
|
| ## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:-------------------:| |
| | No log | 1.0 | 250 | 0.3489 | {'accuracy': 0.864} | |
| | 0.4170 | 2.0 | 500 | 0.5439 | {'accuracy': 0.856} | |
| | 0.4170 | 3.0 | 750 | 0.4622 | {'accuracy': 0.895} | |
| | 0.1997 | 4.0 | 1000 | 0.6808 | {'accuracy': 0.88} | |
| | 0.1997 | 5.0 | 1250 | 0.8102 | {'accuracy': 0.878} | |
| | 0.0662 | 6.0 | 1500 | 0.8642 | {'accuracy': 0.892} | |
| | 0.0662 | 7.0 | 1750 | 0.9038 | {'accuracy': 0.88} | |
| | 0.0103 | 8.0 | 2000 | 0.9522 | {'accuracy': 0.87} | |
| | 0.0103 | 9.0 | 2250 | 0.9865 | {'accuracy': 0.878} | |
| | 0.0066 | 10.0 | 2500 | 0.9717 | {'accuracy': 0.872} | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.18.1 |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu130 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
