mmaguero/gn-offensive-language-identification
Viewer • Updated • 2.17k • 44
How to use mmaguero/toxic-gn-bert-tiny-cased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mmaguero/toxic-gn-bert-tiny-cased") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mmaguero/toxic-gn-bert-tiny-cased")
model = AutoModelForSequenceClassification.from_pretrained("mmaguero/toxic-gn-bert-tiny-cased")This model is a fine-tuned version of mmaguero/gn-bert-tiny-cased on mmaguero/gn-offensive-language-identification dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 87 | 0.3798 | 0.8649 |
| No log | 2.0 | 174 | 0.3606 | 0.8649 |
| No log | 3.0 | 261 | 0.3317 | 0.8879 |
| No log | 4.0 | 348 | 0.3102 | 0.8966 |
| No log | 5.0 | 435 | 0.2947 | 0.8994 |
| 0.3717 | 6.0 | 522 | 0.2853 | 0.9023 |
| 0.3717 | 7.0 | 609 | 0.2800 | 0.8879 |
| 0.3717 | 8.0 | 696 | 0.2788 | 0.8851 |
| 0.3717 | 9.0 | 783 | 0.2777 | 0.8822 |
| 0.3717 | 10.0 | 870 | 0.2777 | 0.8822 |
Base model
mmaguero/gn-bert-tiny-cased