google-research-datasets/paws-x
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How to use semindan/paws_x_m_bert_only_zh 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_zh") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("semindan/paws_x_m_bert_only_zh")
model = AutoModelForSequenceClassification.from_pretrained("semindan/paws_x_m_bert_only_zh")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 |
|---|---|---|---|---|
| 0.4747 | 1.0 | 386 | 0.4424 | 0.807 |
| 0.2681 | 2.0 | 772 | 0.4185 | 0.829 |
| 0.1883 | 3.0 | 1158 | 0.4540 | 0.8305 |
| 0.1416 | 4.0 | 1544 | 0.4700 | 0.8315 |
| 0.111 | 5.0 | 1930 | 0.5074 | 0.8235 |
| 0.0848 | 6.0 | 2316 | 0.6054 | 0.8325 |
| 0.0696 | 7.0 | 2702 | 0.6651 | 0.8335 |
| 0.0555 | 8.0 | 3088 | 0.6952 | 0.8345 |
| 0.046 | 9.0 | 3474 | 0.8017 | 0.8355 |
| 0.0405 | 10.0 | 3860 | 0.7979 | 0.835 |