google-research-datasets/paws-x
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How to use semindan/paws_x_m_bert_only_ja 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_ja") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("semindan/paws_x_m_bert_only_ja")
model = AutoModelForSequenceClassification.from_pretrained("semindan/paws_x_m_bert_only_ja")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 |
|---|---|---|---|---|
| 0.4839 | 1.0 | 386 | 0.4311 | 0.791 |
| 0.2888 | 2.0 | 772 | 0.4328 | 0.8115 |
| 0.2095 | 3.0 | 1158 | 0.4820 | 0.8255 |
| 0.1604 | 4.0 | 1544 | 0.4594 | 0.832 |
| 0.1251 | 5.0 | 1930 | 0.5119 | 0.829 |
| 0.0956 | 6.0 | 2316 | 0.5388 | 0.8335 |
| 0.0791 | 7.0 | 2702 | 0.5696 | 0.834 |
| 0.064 | 8.0 | 3088 | 0.6405 | 0.837 |
| 0.0546 | 9.0 | 3474 | 0.6916 | 0.833 |
| 0.0464 | 10.0 | 3860 | 0.7244 | 0.831 |