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POC - BLOOM for QuestionAnswering, tuned on squad_v2

This model is a fine-tuned version of bigscience/bloom-560m on the squad_v2 dataset. It is intended for a proof of concept, and perhaps to serve as a starting point for others trying to do the same thing.

Ongoing discussion surrounding this effort:


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: 3e-05
  • train_batch_size: 6
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2.0
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • Transformers 4.24.0.dev0
  • Pytorch 1.12.1+cu102
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Question Answering
This model can be loaded on the Inference API on-demand.

Dataset used to train jasoneden/bloom560m-squad-helloworld