Tural/How_to_fine-tune_a_model_for_common_downstream_tasks_V3

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Howtofine-tuneamodelforcommondownstreamtasks_V3

This model is a fine-tuned version of bert-base-uncased on the squad dataset. It achieves the following results on the evaluation set:

• —Loss: 1.0517

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
• —trainbatchsize: 24
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.34.0
• —Pytorch 2.0.0
• —Datasets 2.14.5
• —Tokenizers 0.14.1