klue/klue
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How to use ys7yoo/sts_klue_roberta_large_ep3_ckpt with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ys7yoo/sts_klue_roberta_large_ep3_ckpt") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ys7yoo/sts_klue_roberta_large_ep3_ckpt")
model = AutoModelForSequenceClassification.from_pretrained("ys7yoo/sts_klue_roberta_large_ep3_ckpt", device_map="auto")This model is a fine-tuned version of klue/roberta-large 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 |
|---|---|---|---|---|---|---|
| 0.8931 | 1.0 | 183 | 0.9154 | 0.9154 | 0.7299 | 0.5808 |
| 0.1687 | 2.0 | 366 | 0.3683 | 0.3683 | 0.4665 | 0.8314 |
| 0.0959 | 3.0 | 549 | 0.3655 | 0.3655 | 0.4543 | 0.8326 |
Base model
klue/roberta-large