klue/klue
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How to use ys7yoo/sts_klue_bert_base_ep5_ckpt with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ys7yoo/sts_klue_bert_base_ep5_ckpt") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ys7yoo/sts_klue_bert_base_ep5_ckpt")
model = AutoModelForSequenceClassification.from_pretrained("ys7yoo/sts_klue_bert_base_ep5_ckpt", device_map="auto")This model is a fine-tuned version of klue/bert-base on the klue 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 | Mse | Mae | R2 |
|---|---|---|---|---|---|---|
| 0.8186 | 1.0 | 183 | 0.5172 | 0.5172 | 0.5566 | 0.7631 |
| 0.1529 | 2.0 | 366 | 0.4698 | 0.4698 | 0.5155 | 0.7849 |
| 0.0967 | 3.0 | 549 | 0.4525 | 0.4525 | 0.4859 | 0.7928 |
| 0.0699 | 4.0 | 732 | 0.4232 | 0.4232 | 0.4839 | 0.8062 |
| 0.0537 | 5.0 | 915 | 0.4295 | 0.4295 | 0.4938 | 0.8033 |
Base model
klue/bert-base