# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Yannis98/squad_v2_albert_xxl_finetuned")# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Yannis98/squad_v2_albert_xxl_finetuned")
model = AutoModelForQuestionAnswering.from_pretrained("Yannis98/squad_v2_albert_xxl_finetuned")Quick Links
XXL-Albert-squadv2
This model is a fine-tuned version of Yannis98/XXL-Albert-squadv2 on the rajpurkar/squad_v2 dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 512
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2.0
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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