Edit model card

aristo-roberta-finetuned-csqa

This model is a fine-tuned version of LIAMF-USP/aristo-roberta on the commonsense_qa dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2187
  • Accuracy: 0.7305

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-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • 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
1.131 1.0 609 0.7109 0.7232
0.6957 2.0 1218 0.6912 0.7346
0.459 3.0 1827 0.8364 0.7305
0.3063 4.0 2436 1.0595 0.7322
0.2283 5.0 3045 1.2187 0.7305

Framework versions

  • Transformers 4.9.0
  • Pytorch 1.9.0
  • Datasets 1.10.2
  • Tokenizers 0.10.3
Downloads last month
468

Dataset used to train danlou/aristo-roberta-finetuned-csqa