google/xtreme
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How to use huggingbase/xlm-roberta-base-finetuned-panx-en 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-en") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-en")
model = AutoModelForTokenClassification.from_pretrained("huggingbase/xlm-roberta-base-finetuned-panx-en", 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 |
|---|---|---|---|---|
| 1.1347 | 1.0 | 50 | 0.5771 | 0.4880 |
| 0.5066 | 2.0 | 100 | 0.4209 | 0.6582 |
| 0.3631 | 3.0 | 150 | 0.4043 | 0.6886 |