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sinakhat/distilbert-base-uncased-lora-text-classification
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---
library_name: peft
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
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
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# 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: 1.0332
- 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: Use OptimizerNames.ADAMW_TORCH 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 | 0.4714 | {'accuracy': 0.861} |
| 0.4431 | 2.0 | 500 | 0.4376 | {'accuracy': 0.879} |
| 0.4431 | 3.0 | 750 | 0.6543 | {'accuracy': 0.874} |
| 0.2114 | 4.0 | 1000 | 0.6353 | {'accuracy': 0.888} |
| 0.2114 | 5.0 | 1250 | 0.8143 | {'accuracy': 0.881} |
| 0.0603 | 6.0 | 1500 | 0.8727 | {'accuracy': 0.894} |
| 0.0603 | 7.0 | 1750 | 0.9625 | {'accuracy': 0.887} |
| 0.0297 | 8.0 | 2000 | 0.9678 | {'accuracy': 0.89} |
| 0.0297 | 9.0 | 2250 | 1.0445 | {'accuracy': 0.888} |
| 0.0057 | 10.0 | 2500 | 1.0332 | {'accuracy': 0.89} |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0