google/xtreme
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How to use huggingbase/xlm-roberta-base-finetuned-panx-de with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="huggingbase/xlm-roberta-base-finetuned-panx-de") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-de")
model = AutoModelForTokenClassification.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-de", device_map="auto")This model is a fine-tuned version of xlm-roberta-base on the xtreme 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 | F1 |
|---|---|---|---|---|
| 0.2553 | 1.0 | 525 | 0.1575 | 0.8279 |
| 0.1284 | 2.0 | 1050 | 0.1386 | 0.8463 |
| 0.0813 | 3.0 | 1575 | 0.1365 | 0.8649 |