google/xtreme
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How to use radev/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="radev/xlm-roberta-base-finetuned-panx-de") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("radev/xlm-roberta-base-finetuned-panx-de")
model = AutoModelForTokenClassification.from_pretrained("radev/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 |
|---|---|---|---|---|
| No log | 1.0 | 263 | 0.1807 | 0.8065 |
| 0.2218 | 2.0 | 526 | 0.1365 | 0.8485 |
| 0.2218 | 3.0 | 789 | 0.1345 | 0.8593 |