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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0503
- Accuracy: {'accuracy': 0.888}
## 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 | 0.5703 | {'accuracy': 0.841} |
| 0.416 | 2.0 | 500 | 0.3604 | {'accuracy': 0.889} |
| 0.416 | 3.0 | 750 | 0.6394 | {'accuracy': 0.884} |
| 0.1901 | 4.0 | 1000 | 0.7093 | {'accuracy': 0.885} |
| 0.1901 | 5.0 | 1250 | 0.7750 | {'accuracy': 0.885} |
| 0.044 | 6.0 | 1500 | 0.9100 | {'accuracy': 0.888} |
| 0.044 | 7.0 | 1750 | 1.0710 | {'accuracy': 0.887} |
| 0.0151 | 8.0 | 2000 | 1.0063 | {'accuracy': 0.888} |
| 0.0151 | 9.0 | 2250 | 1.0483 | {'accuracy': 0.892} |
| 0.0107 | 10.0 | 2500 | 1.0503 | {'accuracy': 0.888} |
### Framework versions
- PEFT 0.18.1
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2 |