bert-base-uncased-finetuned-lora-tweet_eval_irony
This model is a fine-tuned version of bert-base-uncased on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.6660
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 |
---|---|---|
0.4775 | None | 0 |
0.5654 | 0.6976 | 0 |
0.6115 | 0.6567 | 1 |
0.6241 | 0.6117 | 2 |
0.6649 | 0.5838 | 3 |
0.6471 | 0.5611 | 4 |
0.6440 | 0.5594 | 5 |
0.6576 | 0.5457 | 6 |
0.6660 | 0.5372 | 7 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2
- Downloads last month
- 1
Inference API (serverless) does not yet support peft models for this pipeline type.
Model tree for TransferGraph/bert-base-uncased-finetuned-lora-tweet_eval_irony
Base model
google-bert/bert-base-uncasedDataset used to train TransferGraph/bert-base-uncased-finetuned-lora-tweet_eval_irony
Evaluation results
- accuracy on tweet_evalvalidation set self-reported0.666