log-anomaly-detection-model-roberta
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1524
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: 8
- 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_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.183 | 1.0 | 10482 | 0.1558 |
| 0.0091 | 2.0 | 20964 | 0.1585 |
| 0.1212 | 3.0 | 31446 | 0.1524 |
| 0.0653 | 4.0 | 41928 | 0.1524 |
| 0.3581 | 5.0 | 52410 | 0.1545 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for Dumi2025/log-anomaly-detection-model-roberta
Base model
FacebookAI/roberta-base