IIC/socialdisner
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How to use IIC/xlm-roberta-large-socialdisner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="IIC/xlm-roberta-large-socialdisner") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("IIC/xlm-roberta-large-socialdisner")
model = AutoModelForSequenceClassification.from_pretrained("IIC/xlm-roberta-large-socialdisner")This model is a finetuned version of xlm-roberta-large for the socialdisner dataset used in a benchmark in the paper TODO. The model has a F1 of 0.941
Please refer to the original publication for more information TODO LINK
| parameter | Value |
|---|---|
| batch size | 64 |
| learning rate | 3e-05 |
| classifier dropout | 0.2 |
| warmup ratio | 0 |
| warmup steps | 0 |
| weight decay | 0 |
| optimizer | AdamW |
| epochs | 10 |
| early stopping patience | 3 |
TODO