bert_train_book_ent_15p_mid_wnli
This model is a fine-tuned version of gokulsrinivasagan/bert_train_book_ent_15p_mid on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6854
- Accuracy: 0.5634
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 |
|---|---|---|---|---|
| 0.7086 | 1.0 | 3 | 0.6898 | 0.5634 |
| 0.7213 | 2.0 | 6 | 0.6862 | 0.5634 |
| 0.699 | 3.0 | 9 | 0.6976 | 0.4366 |
| 0.6982 | 4.0 | 12 | 0.7079 | 0.4366 |
| 0.6992 | 5.0 | 15 | 0.6951 | 0.4366 |
| 0.6953 | 6.0 | 18 | 0.6882 | 0.5634 |
| 0.6986 | 7.0 | 21 | 0.6854 | 0.5634 |
| 0.6991 | 8.0 | 24 | 0.6903 | 0.5634 |
| 0.6941 | 9.0 | 27 | 0.6972 | 0.4366 |
| 0.6926 | 10.0 | 30 | 0.6951 | 0.4366 |
| 0.6981 | 11.0 | 33 | 0.6896 | 0.5634 |
| 0.6941 | 12.0 | 36 | 0.6901 | 0.5634 |
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_train_book_ent_15p_mid_wnli
Base model
distilbert/distilbert-base-uncasedDataset used to train gokulsrinivasagan/bert_train_book_ent_15p_mid_wnli
Evaluation results
- Accuracy on GLUE WNLIself-reported0.563