peft_ft_random / README.md
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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
model-index:
  - name: peft_ft_random
    results: []

peft_ft_random

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

  • Loss: 8.4980
  • Accuracy: -5564.7596

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: 0.005
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.8 2 10.1306 48758.8852
No log 2.0 5 9.1696 68666.5148
No log 2.8 7 8.8054 -22131.0614
9.5148 4.0 10 8.4980 -5564.7596

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1