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gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of gchhablani/bert-base-cased-finetuned-wnli on the tweet_eval dataset. It achieves the following results on the evaluation set:

  • accuracy: 0.6618

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: 0.0005
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

accuracy train_loss epoch
0.5225 None 0
0.5801 0.7086 0
0.5529 0.6679 1
0.6052 0.6339 2
0.6440 0.6083 3
0.6461 0.5908 4
0.6293 0.5716 5
0.6534 0.5522 6
0.6618 0.5513 7

Framework versions

  • PEFT 0.8.2
  • Transformers 4.37.2
  • Pytorch 2.2.0
  • Datasets 2.16.1
  • Tokenizers 0.15.2
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Adapter for

Dataset used to train TransferGraph/gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_irony

Evaluation results