|
---
|
|
library_name: transformers
|
|
license: mit
|
|
base_model: FacebookAI/roberta-base
|
|
tags:
|
|
- generated_from_trainer
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: LLMGUARD-roberta-11
|
|
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. -->
|
|
|
|
# LLMGUARD-roberta-11
|
|
|
|
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.5908
|
|
- Accuracy: 0.8020
|
|
|
|
## 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: 2e-06
|
|
- train_batch_size: 16
|
|
- eval_batch_size: 8
|
|
- seed: 42
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
|
- lr_scheduler_type: linear
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
- num_epochs: 8
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 1.203 | 1.0 | 1585 | 0.8223 | 0.7612 |
|
|
| 0.696 | 2.0 | 3170 | 0.6380 | 0.7964 |
|
|
| 0.6014 | 3.0 | 4755 | 0.6126 | 0.7997 |
|
|
| 0.5652 | 4.0 | 6340 | 0.5943 | 0.8026 |
|
|
| 0.5346 | 5.0 | 7925 | 0.5890 | 0.8018 |
|
|
| 0.5118 | 6.0 | 9510 | 0.5860 | 0.8035 |
|
|
| 0.4702 | 7.0 | 11095 | 0.5901 | 0.8034 |
|
|
| 0.489 | 8.0 | 12680 | 0.5908 | 0.8020 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.48.0.dev0
|
|
- Pytorch 2.5.1+cu124
|
|
- Datasets 3.2.0
|
|
- Tokenizers 0.21.0
|
|
|
