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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1492 |
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- Accuracy: {'accuracy': 0.872} |
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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 | 0.4627 | {'accuracy': 0.866} | |
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| 0.3796 | 2.0 | 500 | 0.5169 | {'accuracy': 0.87} | |
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| 0.3796 | 3.0 | 750 | 0.6853 | {'accuracy': 0.871} | |
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| 0.1693 | 4.0 | 1000 | 0.8606 | {'accuracy': 0.869} | |
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| 0.1693 | 5.0 | 1250 | 0.9956 | {'accuracy': 0.868} | |
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| 0.0357 | 6.0 | 1500 | 1.0542 | {'accuracy': 0.868} | |
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| 0.0357 | 7.0 | 1750 | 1.0670 | {'accuracy': 0.868} | |
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| 0.0202 | 8.0 | 2000 | 1.1235 | {'accuracy': 0.87} | |
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| 0.0202 | 9.0 | 2250 | 1.1426 | {'accuracy': 0.871} | |
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| 0.0022 | 10.0 | 2500 | 1.1492 | {'accuracy': 0.872} | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
