bert-base-uncased-finetuned-tquad

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bert-base-uncased-finetuned-tquad

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7603

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2

Pipeline

dataset = load_dataset("dilanbakr/tquad")

tokenizer = AutoTokenizer.from_pretrained("dilanbakr/bert-base-uncased-finetuned-tquad")

model = AutoModelForQuestionAnswering.from_pretrained("dilanbakr/bert-base-uncased-finetuned-tquad")

nlp=pipeline("question-answering", model=model, tokenizer=tokenizer)

print(nlp(question="Anaheim hangi ülkenin rock grubudur?", context="Anaheim, Kaliforniya'da kurulmuş olan Amerikan rock grubudur."))