bart-large-bn-adapter-3.17M-snli-model1

This model is a fine-tuned version of facebook/bart-large on the snli dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2388
  • Accuracy: 0.9191

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: 32
  • eval_batch_size: 32
  • seed: 36
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3308 1.0 17168 0.2528 0.9099
0.3118 2.0 34336 0.2433 0.9163
0.3133 3.0 51504 0.2388 0.9191

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model's library. Check the docs .

Model tree for varun-v-rao/bart-large-bn-adapter-3.17M-snli-model1

Finetuned
(145)
this model

Dataset used to train varun-v-rao/bart-large-bn-adapter-3.17M-snli-model1

Evaluation results