megagonlabs/subjqa
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How to use Chetna19/bart-large-finetuned-squadv1_qa_model 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="Chetna19/bart-large-finetuned-squadv1_qa_model") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Chetna19/bart-large-finetuned-squadv1_qa_model")
model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/bart-large-finetuned-squadv1_qa_model", device_map="auto")This model is a fine-tuned version of valhalla/bart-large-finetuned-squadv1 on the subjqa 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 |
|---|---|---|---|
| 4.2299 | 1.0 | 32 | 4.8220 |
| 4.1974 | 2.0 | 64 | 4.7695 |
| 4.1692 | 3.0 | 96 | 4.7263 |
| 4.1427 | 4.0 | 128 | 4.7136 |