google-research-datasets/paws-x
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How to use semindan/paws_x_m_bert_only_en with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="semindan/paws_x_m_bert_only_en") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("semindan/paws_x_m_bert_only_en")
model = AutoModelForSequenceClassification.from_pretrained("semindan/paws_x_m_bert_only_en")This model is a fine-tuned version of bert-base-multilingual-cased on the paws-x 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 |
|---|---|---|---|---|
| 0.3185 | 1.0 | 772 | 0.2330 | 0.916 |
| 0.1484 | 2.0 | 1544 | 0.2518 | 0.9205 |
| 0.1013 | 3.0 | 2316 | 0.2902 | 0.921 |
| 0.0735 | 4.0 | 3088 | 0.2797 | 0.9265 |
| 0.0544 | 5.0 | 3860 | 0.2789 | 0.9315 |
| 0.0406 | 6.0 | 4632 | 0.3514 | 0.929 |
| 0.0313 | 7.0 | 5404 | 0.3799 | 0.926 |
| 0.022 | 8.0 | 6176 | 0.4567 | 0.9255 |
| 0.0156 | 9.0 | 6948 | 0.4652 | 0.9275 |
| 0.0123 | 10.0 | 7720 | 0.4996 | 0.925 |