google/xtreme
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How to use patnelt60/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="patnelt60/xlm-roberta-base-finetuned-panx-fr") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("patnelt60/xlm-roberta-base-finetuned-panx-fr")
model = AutoModelForTokenClassification.from_pretrained("patnelt60/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 |
|---|---|---|---|---|
| No log | 1.0 | 24 | 0.5559 | 0.6516 |
| No log | 2.0 | 48 | 0.3394 | 0.7818 |
| No log | 3.0 | 72 | 0.2994 | 0.8059 |
| No log | 4.0 | 96 | 0.2888 | 0.8221 |
| No log | 5.0 | 120 | 0.2853 | 0.8326 |
| No log | 6.0 | 144 | 0.2814 | 0.8324 |
Base model
FacebookAI/xlm-roberta-base