Hate-speech-CNERG/hatexplain
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How to use uboza10300/gpt2-hatexplain with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="uboza10300/gpt2-hatexplain") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("uboza10300/gpt2-hatexplain")
model = AutoModelForSequenceClassification.from_pretrained("uboza10300/gpt2-hatexplain")This model is a fine-tuned version of gpt2 on the hatexplain dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7396 | 1.0 | 962 | 0.7567 | 0.6790 | 0.6713 | 0.6790 | 0.6641 |
| 0.6697 | 2.0 | 1924 | 0.7486 | 0.6842 | 0.6769 | 0.6842 | 0.6783 |
| 0.7573 | 3.0 | 2886 | 0.7685 | 0.6748 | 0.6658 | 0.6748 | 0.6656 |
Base model
openai-community/gpt2