testing_fine_tune_qa

This model is a fine-tuned version of bigscience/bloom-3b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1709

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss
1.9148 0.4 200 1.6602
1.6726 0.8 400 1.3506
1.0625 1.2 600 1.2383
0.8001 1.6 800 1.1885
0.3615 2.0 1000 1.1709

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.0
  • Tokenizers 0.15.0
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