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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Model tree for TransferGraph/gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_hate
Base model
gchhablani/bert-base-cased-finetuned-wnliDataset used to train TransferGraph/gchhablani_bert-base-cased-finetuned-wnli-finetuned-lora-tweet_eval_hate
Evaluation results
- accuracy on tweet_evalvalidation set self-reported0.708