metadata
library_name: peft
license: mit
base_model: roberta-large
tags:
- base_model:adapter:roberta-large
- lora
- transformers
model-index:
- name: TON_IoT_no_scanning_LoRA
results: []
TON_IoT_no_scanning_LoRA
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0024
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 94 | 0.2305 |
| No log | 2.0 | 188 | 0.0076 |
| No log | 3.0 | 282 | 0.0082 |
| No log | 4.0 | 376 | 0.0063 |
| No log | 5.0 | 470 | 0.0059 |
| 0.1156 | 6.0 | 564 | 0.0053 |
| 0.1156 | 7.0 | 658 | 0.0036 |
| 0.1156 | 8.0 | 752 | 0.0024 |
| 0.1156 | 9.0 | 846 | 0.0025 |
| 0.1156 | 10.0 | 940 | 0.0024 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.2.0
- Tokenizers 0.22.1