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---
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library_name: peft
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilbert-base-uncased-lora-text-classification
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilbert-base-uncased-lora-text-classification |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9980 |
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- Accuracy: {'accuracy': 0.884} |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------:| |
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| No log | 1.0 | 250 | 0.3876 | {'accuracy': 0.88} | |
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| 0.452 | 2.0 | 500 | 0.4465 | {'accuracy': 0.864} | |
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| 0.452 | 3.0 | 750 | 0.4792 | {'accuracy': 0.882} | |
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| 0.2137 | 4.0 | 1000 | 0.7374 | {'accuracy': 0.883} | |
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| 0.2137 | 5.0 | 1250 | 0.8041 | {'accuracy': 0.886} | |
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| 0.0584 | 6.0 | 1500 | 0.8809 | {'accuracy': 0.89} | |
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| 0.0584 | 7.0 | 1750 | 0.8800 | {'accuracy': 0.887} | |
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| 0.0275 | 8.0 | 2000 | 0.9635 | {'accuracy': 0.885} | |
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| 0.0275 | 9.0 | 2250 | 1.0078 | {'accuracy': 0.882} | |
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| 0.0142 | 10.0 | 2500 | 0.9980 | {'accuracy': 0.884} | |
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### Framework versions |
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- PEFT 0.15.1 |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cpu |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
