google/xtreme
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How to use nerdai/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="nerdai/xlm-roberta-base-finetuned-panx-de") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("nerdai/xlm-roberta-base-finetuned-panx-de")
model = AutoModelForTokenClassification.from_pretrained("nerdai/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 |
|---|---|---|---|---|
| 0.2577 | 1.0 | 968 | 0.1638 | 0.8190 |
| 0.1303 | 2.0 | 1936 | 0.1428 | 0.8526 |
| 0.0795 | 3.0 | 2904 | 0.1502 | 0.8666 |