bert_base_train_book_ent_15p_s_init_qqp
This model is a fine-tuned version of gokulsrinivasagan/bert_base_train_book_ent_15p_s_init on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.6573
- Accuracy: 0.6318
- F1: 0.0
- Combined Score: 0.3159
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 |
---|---|---|---|---|---|---|
0.662 | 1.0 | 1422 | 0.6602 | 0.6318 | 0.0 | 0.3159 |
0.6607 | 2.0 | 2844 | 0.6573 | 0.6318 | 0.0 | 0.3159 |
0.6602 | 3.0 | 4266 | 0.6597 | 0.6318 | 0.0 | 0.3159 |
0.6601 | 4.0 | 5688 | 0.6595 | 0.6318 | 0.0 | 0.3159 |
0.6595 | 5.0 | 7110 | 0.6582 | 0.6318 | 0.0 | 0.3159 |
0.6595 | 6.0 | 8532 | 0.6578 | 0.6318 | 0.0 | 0.3159 |
0.6594 | 7.0 | 9954 | 0.6590 | 0.6318 | 0.0 | 0.3159 |
Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for gokulsrinivasagan/bert_base_train_book_ent_15p_s_init_qqp
Base model
google-bert/bert-base-uncasedDataset used to train gokulsrinivasagan/bert_base_train_book_ent_15p_s_init_qqp
Evaluation results
- Accuracy on GLUE QQPself-reported0.632
- F1 on GLUE QQPself-reported0.000