google-research-datasets/paws-x
Viewer • Updated • 374k • 3.8k • 51
How to use semindan/paws_x_m_bert_only_ko 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_ko") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("semindan/paws_x_m_bert_only_ko")
model = AutoModelForSequenceClassification.from_pretrained("semindan/paws_x_m_bert_only_ko")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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5446 | 1.0 | 386 | 0.4837 | 0.768 |
| 0.3443 | 2.0 | 772 | 0.4530 | 0.8125 |
| 0.258 | 3.0 | 1158 | 0.4496 | 0.8145 |
| 0.2023 | 4.0 | 1544 | 0.4944 | 0.81 |
| 0.1581 | 5.0 | 1930 | 0.5040 | 0.814 |
| 0.1263 | 6.0 | 2316 | 0.5937 | 0.8145 |
| 0.1041 | 7.0 | 2702 | 0.6578 | 0.8115 |
| 0.0828 | 8.0 | 3088 | 0.6841 | 0.8215 |
| 0.0697 | 9.0 | 3474 | 0.7239 | 0.82 |
| 0.0596 | 10.0 | 3860 | 0.7649 | 0.8215 |