metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: roberta-large
metrics:
- accuracy
model-index:
- name: lora-roberta-large-finetuned-reduced_captures
results: []
language:
- en
lora-roberta-large-finetuned-reduced_captures
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2458
- Accuracy: 0.9345
Tests metrics:
- loss: 0.23798689246177673
- accuracy: 0.9321285694578563
Model description
Captures prediction based on LoRA-adapted RoBERTa-large. This includes labels 0-12 but excluding 9 (criminality).
Intended uses & limitations
Impero Safeguarding & Wellbeing
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 |
|---|---|---|---|---|
| 0.3924 | 0.9996 | 616 | 0.3862 | 0.8906 |
| 0.4385 | 1.9992 | 1232 | 0.3267 | 0.9048 |
| 0.388 | 2.9988 | 1848 | 0.2849 | 0.9175 |
| 0.3256 | 4.0 | 2465 | 0.2728 | 0.9207 |
| 0.2718 | 4.9996 | 3081 | 0.2939 | 0.9170 |
| 0.2877 | 5.9992 | 3697 | 0.2522 | 0.9267 |
| 0.233 | 6.9988 | 4313 | 0.2624 | 0.9260 |
| 0.1832 | 8.0 | 4930 | 0.2512 | 0.9317 |
| 0.2399 | 8.9996 | 5546 | 0.2458 | 0.9345 |
| 0.1506 | 9.9959 | 6160 | 0.2390 | 0.9336 |
Framework versions
- PEFT 0.12.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.0