ChrisZeng's picture
update model card README.md
380f7c8
metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: electra-large-discriminator-nli-efl-tweeteval
    results: []

electra-large-discriminator-nli-efl-tweeteval

This model is a fine-tuned version of ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli on the None dataset. It achieves the following results on the evaluation set:

  • Accuracy: 0.7943
  • F1: 0.7872
  • Loss: 0.3004

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: 1e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • 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 Accuracy F1 Validation Loss
0.4384 1.0 163 0.7444 0.7308 0.3962
0.3447 2.0 326 0.7659 0.7552 0.3410
0.3057 3.0 489 0.7750 0.7688 0.3234
0.287 4.0 652 0.7857 0.7779 0.3069
0.2742 5.0 815 0.7887 0.7822 0.3030
0.2676 6.0 978 0.7939 0.7851 0.2982
0.2585 7.0 1141 0.7909 0.7822 0.3002
0.2526 8.0 1304 0.7943 0.7876 0.3052
0.2479 9.0 1467 0.7939 0.7847 0.2997
0.2451 10.0 1630 0.7956 0.7873 0.3014
0.2397 11.0 1793 0.7943 0.7872 0.3004

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.12.0.dev20220417
  • Datasets 2.1.0
  • Tokenizers 0.10.3