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--- |
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license: apache-2.0 |
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model-index: |
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- name: roberta-base-spam-detector |
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results: [] |
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datasets: |
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- 0x7194633/spam_detector |
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language: |
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- en |
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metrics: |
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- accuracy |
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pipeline_tag: text-classification |
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--- |
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# roberta-base-spam-detector |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [0x7194633/spam_detector](https://huggingface.co/datasets/0x7194633/spam_detector) dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.0211 |
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- eval_accuracy: 0.9979 |
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- eval_f1: 0.9980 |
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- eval_precision: 0.9960 |
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- eval_recall: 1.0 |
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- eval_runtime: 30.7625 |
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- eval_samples_per_second: 30.882 |
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- eval_steps_per_second: 1.95 |
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- epoch: 1.16 |
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- step: 1446 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3 |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
