| ---
|
| library_name: peft
|
| license: mit
|
| base_model: roberta-base
|
| tags:
|
| - generated_from_trainer
|
| metrics:
|
| - accuracy
|
| model-index:
|
| - name: roberta-base-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. --> |
|
|
| # roberta-base-lora-text-classification |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2259 |
| - Accuracy: {'accuracy': 0.9357798165137615} |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use 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: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:| |
| | 0.268 | 1.0 | 4210 | 0.2460 | {'accuracy': 0.908256880733945} | |
| | 0.2589 | 2.0 | 8420 | 0.2230 | {'accuracy': 0.9243119266055045} | |
| | 0.2229 | 3.0 | 12630 | 0.2091 | {'accuracy': 0.926605504587156} | |
| | 0.2068 | 4.0 | 16840 | 0.2403 | {'accuracy': 0.9277522935779816} | |
| | 0.1923 | 5.0 | 21050 | 0.2259 | {'accuracy': 0.9357798165137615} | |
|
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|
|
| ### Framework versions |
|
|
| - PEFT 0.14.0 |
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu118 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
