google-research-datasets/tydiqa
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How to use krinal214/xlm-all with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "question-answering" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# pip install "transformers<5.0.0"
from transformers import pipeline
pipe = pipeline("question-answering", model="krinal214/xlm-all") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("krinal214/xlm-all")
model = AutoModelForQuestionAnswering.from_pretrained("krinal214/xlm-all", device_map="auto")This model is a fine-tuned version of xlm-roberta-base on the tydiqa 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 |
|---|---|---|---|
| 1.4483 | 1.0 | 3381 | 0.6038 |