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outputs
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0041
- Pearson: 0.9845
Model description
O modelo verifica se a mensagem é spam o não. Caso o valor seja maior ou igual a 0.6 ele é spam, caso seja menor ele não é spam.
Aqui temos algumas mensagens do dataframe de teste:
- Send a logo 2 ur lover - 2 names joined by a heart. Txt LOVE NAME1 NAME2 MOBNO eg LOVE ADAM EVE 07123456789 to 87077 Yahoo! POBox36504W45WQ TxtNO 4 no ads 150p | Spam
- Not directly behind... Abt 4 rows behind ü... | Non-Spam
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 8e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson |
|---|---|---|---|---|
| No log | 1.0 | 24 | 0.0338 | 0.9274 |
| No log | 2.0 | 48 | 0.0070 | 0.9667 |
| No log | 3.0 | 72 | 0.0110 | 0.9504 |
| No log | 4.0 | 96 | 0.0078 | 0.9634 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
