gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_hate

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: 0.708

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: 0.0004
  • 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: 4

Training results

accuracy train_loss epoch
0.573 None 0
0.687 0.6008 0
0.699 0.5004 1
0.7 0.4675 2
0.708 0.4508 3

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

Evaluation results