bert_tiny_lda_100_v1_book_qqp
This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_lda_100_v1_book on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.3060
- Accuracy: 0.8700
- F1: 0.8219
- Combined Score: 0.8459
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
---|---|---|---|---|---|---|
0.4139 | 1.0 | 1422 | 0.3737 | 0.8295 | 0.7418 | 0.7857 |
0.3158 | 2.0 | 2844 | 0.3214 | 0.8611 | 0.8107 | 0.8359 |
0.2619 | 3.0 | 4266 | 0.3060 | 0.8700 | 0.8219 | 0.8459 |
0.218 | 4.0 | 5688 | 0.3371 | 0.8694 | 0.8117 | 0.8405 |
0.1821 | 5.0 | 7110 | 0.3295 | 0.8787 | 0.8341 | 0.8564 |
0.1502 | 6.0 | 8532 | 0.3353 | 0.8790 | 0.8389 | 0.8589 |
0.1258 | 7.0 | 9954 | 0.3609 | 0.8776 | 0.8375 | 0.8576 |
0.105 | 8.0 | 11376 | 0.4070 | 0.8786 | 0.8329 | 0.8558 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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Model tree for gokulsrinivasagan/bert_tiny_lda_100_v1_book_qqp
Base model
gokulsrinivasagan/bert_tiny_lda_100_v1_bookDataset used to train gokulsrinivasagan/bert_tiny_lda_100_v1_book_qqp
Evaluation results
- Accuracy on GLUE QQPself-reported0.870
- F1 on GLUE QQPself-reported0.822