google-research-datasets/paws-x
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How to use semindan/paws_x_m_bert_only_es 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_es") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("semindan/paws_x_m_bert_only_es")
model = AutoModelForSequenceClassification.from_pretrained("semindan/paws_x_m_bert_only_es")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 |
|---|---|---|---|---|
| 0.4197 | 1.0 | 386 | 0.3860 | 0.843 |
| 0.2041 | 2.0 | 772 | 0.3299 | 0.8755 |
| 0.1389 | 3.0 | 1158 | 0.3597 | 0.88 |
| 0.1027 | 4.0 | 1544 | 0.3851 | 0.878 |
| 0.0779 | 5.0 | 1930 | 0.4119 | 0.8815 |
| 0.0631 | 6.0 | 2316 | 0.4387 | 0.8865 |
| 0.0517 | 7.0 | 2702 | 0.4643 | 0.888 |
| 0.0416 | 8.0 | 3088 | 0.4944 | 0.887 |
| 0.0364 | 9.0 | 3474 | 0.5478 | 0.8845 |
| 0.0297 | 10.0 | 3860 | 0.5894 | 0.883 |