metadata
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: []
distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of 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