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---
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: 0.9743
- Accuracy: {'accuracy': 0.89}
## 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 | 0.5011 | {'accuracy': 0.849} |
| 0.4507 | 2.0 | 500 | 0.3976 | {'accuracy': 0.887} |
| 0.4507 | 3.0 | 750 | 0.5992 | {'accuracy': 0.891} |
| 0.1928 | 4.0 | 1000 | 0.6172 | {'accuracy': 0.897} |
| 0.1928 | 5.0 | 1250 | 0.7082 | {'accuracy': 0.89} |
| 0.0827 | 6.0 | 1500 | 0.8177 | {'accuracy': 0.89} |
| 0.0827 | 7.0 | 1750 | 0.8743 | {'accuracy': 0.886} |
| 0.0127 | 8.0 | 2000 | 0.9673 | {'accuracy': 0.892} |
| 0.0127 | 9.0 | 2250 | 0.9793 | {'accuracy': 0.89} |
| 0.0103 | 10.0 | 2500 | 0.9743 | {'accuracy': 0.89} |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |