roberta-base-spam-detector
This model is a fine-tuned version of roberta-base on the 0x7194633/spam_detector dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0211
- eval_accuracy: 0.9979
- eval_f1: 0.9980
- eval_precision: 0.9960
- eval_recall: 1.0
- eval_runtime: 30.7625
- eval_samples_per_second: 30.882
- eval_steps_per_second: 1.95
- epoch: 1.16
- step: 1446
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.