metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: roberta-base
metrics:
- accuracy
model-index:
- name: roberta-base-lora-text-classification
results: []
roberta-base-lora-text-classification
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6577
- Accuracy: {'accuracy': 0.933}
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 | 0.2663 | {'accuracy': 0.936} |
| 0.4315 | 2.0 | 500 | 0.3082 | {'accuracy': 0.934} |
| 0.4315 | 3.0 | 750 | 0.4077 | {'accuracy': 0.937} |
| 0.1531 | 4.0 | 1000 | 0.5257 | {'accuracy': 0.93} |
| 0.1531 | 5.0 | 1250 | 0.5102 | {'accuracy': 0.939} |
| 0.0797 | 6.0 | 1500 | 0.5795 | {'accuracy': 0.934} |
| 0.0797 | 7.0 | 1750 | 0.5838 | {'accuracy': 0.933} |
| 0.0373 | 8.0 | 2000 | 0.6731 | {'accuracy': 0.933} |
| 0.0373 | 9.0 | 2250 | 0.6507 | {'accuracy': 0.938} |
| 0.0218 | 10.0 | 2500 | 0.6577 | {'accuracy': 0.933} |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1