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prompt_fine_tuned_CB_bert
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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
  - accuracy
  - f1
model-index:
  - name: prompt_fine_tuned_CB_bert
    results: []

prompt_fine_tuned_CB_bert

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

  • Loss: 1.3050
  • Accuracy: 0.3182
  • F1: 0.1536

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: 5e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 400

Training results

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1