tweets-hate-speech-detection/tweets_hate_speech_detection
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How to use Arvnd03/FirstTry with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Arvnd03/FirstTry") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Arvnd03/FirstTry")
model = AutoModelForSequenceClassification.from_pretrained("Arvnd03/FirstTry", device_map="auto")This model is a fine-tuned version of roberta-base on the tweets_hate_speech_detection 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 | F1 |
|---|---|---|---|---|---|
| 0.1159 | 1.0 | 1599 | 0.1019 | 0.9759 | 0.8270 |
| 0.0727 | 2.0 | 3198 | 0.0965 | 0.9795 | 0.8424 |
| 0.044 | 3.0 | 4797 | 0.0847 | 0.9822 | 0.8693 |
| 0.0301 | 4.0 | 6396 | 0.1121 | 0.9811 | 0.8660 |
| 0.0206 | 5.0 | 7995 | 0.1718 | 0.9700 | 0.8110 |
| 0.0176 | 6.0 | 9594 | 0.1453 | 0.9811 | 0.8591 |