google/xtreme
Viewer • Updated • 2.77M • 22.4k • 117
How to use smallsuper/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="smallsuper/xlm-roberta-base-finetuned-panx-fr") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("smallsuper/xlm-roberta-base-finetuned-panx-fr")
model = AutoModelForTokenClassification.from_pretrained("smallsuper/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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.793 | 1.0 | 96 | 0.3923 | 0.7447 |
| 0.3258 | 2.0 | 192 | 0.3344 | 0.7790 |
| 0.2251 | 3.0 | 288 | 0.3160 | 0.8095 |
Base model
FacebookAI/xlm-roberta-base