metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- sms_spam
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-spam
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: sms_spam
type: sms_spam
config: plain_text
split: train
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.9946236559139785
- name: F1
type: f1
value: 0.994638201694024
distilbert-base-uncased-finetuned-spam
This model is a fine-tuned version of distilbert-base-uncased on the sms_spam dataset. It achieves the following results on the evaluation set:
- Loss: 0.0260
- Accuracy: 0.9946
- F1: 0.9946
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: 64
- eval_batch_size: 64
- 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 | F1 |
---|---|---|---|---|---|
0.1573 | 1.0 | 79 | 0.0308 | 0.9910 | 0.9910 |
0.0367 | 2.0 | 158 | 0.0260 | 0.9946 | 0.9946 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2