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metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: checkpoint-finetuned-stationary-update
    results: []

checkpoint-finetuned-stationary-update

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

  • Loss: 0.6818
  • Accuracy: 0.8067
  • F1: 0.8027

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
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5971 1.0 38 0.5642 0.72 0.6533
0.4759 2.0 76 0.4484 0.7633 0.7670
0.3768 3.0 114 0.4491 0.8033 0.7924
0.2983 4.0 152 0.4333 0.82 0.8175
0.2111 5.0 190 0.5193 0.8067 0.7990
0.1627 6.0 228 0.5407 0.8133 0.8101
0.1285 7.0 266 0.6347 0.7933 0.7823
0.0966 8.0 304 0.6961 0.8067 0.7973
0.0879 9.0 342 0.6972 0.8133 0.8042
0.0673 10.0 380 0.6818 0.8067 0.8027

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0