tmnam20/VieGLUE
Updated • 52 • 1
How to use tmnam20/xlm-roberta-large-mnli-10 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="tmnam20/xlm-roberta-large-mnli-10") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("tmnam20/xlm-roberta-large-mnli-10")
model = AutoModelForSequenceClassification.from_pretrained("tmnam20/xlm-roberta-large-mnli-10")This model is a fine-tuned version of xlm-roberta-large on the tmnam20/VieGLUE/MNLI 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 |
|---|---|---|---|---|
| 1.1009 | 0.81 | 10000 | 1.1015 | 0.3182 |
| 1.1042 | 1.63 | 20000 | 1.0998 | 0.3182 |
| 1.1034 | 2.44 | 30000 | 1.0985 | 0.3545 |
Base model
FacebookAI/xlm-roberta-large