google/xtreme
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How to use huggingbase/xlm-roberta-base-finetuned-panx-fr 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-fr") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-fr")
model = AutoModelForTokenClassification.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-fr", 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 |
|---|---|---|---|---|
| 0.5779 | 1.0 | 191 | 0.3701 | 0.7701 |
| 0.2735 | 2.0 | 382 | 0.2908 | 0.8254 |
| 0.1769 | 3.0 | 573 | 0.2763 | 0.8346 |