qqp_v2
This model is a fine-tuned version of bert-base-uncased on the quora dataset. It achieves the following results on the evaluation set:
- Loss: 0.2537
- Accuracy: 0.9073
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2591 | 1.0 | 5054 | 0.2429 | 0.8948 |
| 0.186 | 2.0 | 10108 | 0.2342 | 0.9058 |
| 0.1349 | 3.0 | 15162 | 0.2537 | 0.9073 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 14
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for hoganpham/qqp_v2
Base model
google-bert/bert-base-uncased