metadata
license: mit
tags:
- generated_from_trainer
datasets:
- sms_spam
metrics:
- accuracy
base_model: roberta-base
model-index:
- name: roberta-base-finetuned-sms-spam-detection
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: sms_spam
type: sms_spam
args: plain_text
metrics:
- type: accuracy
value: 0.998
name: Accuracy
roberta-base-finetuned-sms-spam-detection
This model is a fine-tuned version of roberta-base on the sms_spam dataset. It achieves the following results on the evaluation set:
- Loss: 0.0133
- Accuracy: 0.998
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0363 | 1.0 | 250 | 0.0156 | 0.996 |
0.0147 | 2.0 | 500 | 0.0133 | 0.998 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0