| --- |
| base_model: distilbert-base-uncased |
| library_name: peft |
| license: apache-2.0 |
| metrics: |
| - accuracy |
| tags: |
| - generated_from_trainer |
| 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 the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.6464 |
| - Accuracy: {'accuracy': 0.84} |
|
|
| ## 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 | 0.5728 | {'accuracy': 0.824} | |
| | 0.4384 | 2.0 | 500 | 0.6861 | {'accuracy': 0.84} | |
| | 0.4384 | 3.0 | 750 | 1.1608 | {'accuracy': 0.812} | |
| | 0.1949 | 4.0 | 1000 | 1.0198 | {'accuracy': 0.826} | |
| | 0.1949 | 5.0 | 1250 | 1.1314 | {'accuracy': 0.838} | |
| | 0.0612 | 6.0 | 1500 | 1.3810 | {'accuracy': 0.844} | |
| | 0.0612 | 7.0 | 1750 | 1.6426 | {'accuracy': 0.832} | |
| | 0.0164 | 8.0 | 2000 | 1.6141 | {'accuracy': 0.844} | |
| | 0.0164 | 9.0 | 2250 | 1.6768 | {'accuracy': 0.842} | |
| | 0.0075 | 10.0 | 2500 | 1.6464 | {'accuracy': 0.84} | |
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|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.42.4 |
| - Pytorch 2.3.1 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
