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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
base_model: google/electra-base-discriminator
model-index:
  - name: electra-base-discriminator-finetuned-3d-sentiment
    results: []

electra-base-discriminator-finetuned-3d-sentiment

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: 0.5887
  • Accuracy: 0.7873
  • Precision: 0.7897
  • Recall: 0.7873
  • F1: 0.7864

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: 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
  • lr_scheduler_warmup_steps: 6381
  • num_epochs: 7
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.797 1.0 1595 0.7075 0.7353 0.7434 0.7353 0.7357
0.5329 2.0 3190 0.6508 0.7550 0.7646 0.7550 0.7554
0.4597 3.0 4785 0.5889 0.7702 0.7803 0.7702 0.7695
0.3918 4.0 6380 0.5887 0.7873 0.7897 0.7873 0.7864
0.3093 5.0 7975 0.6412 0.7833 0.7877 0.7833 0.7836
0.2144 6.0 9570 0.7786 0.7844 0.7900 0.7844 0.7851
0.1507 7.0 11165 0.8455 0.7853 0.7903 0.7853 0.7862

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.10.1
  • Tokenizers 0.13.3