bert-base-uncased-finetune-kggpu
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7939
- Accuracy: 0.8013
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7528 | 1.0 | 2299 | 0.5717 | 0.7772 |
| 0.3795 | 2.0 | 4598 | 0.5832 | 0.7949 |
| 0.1499 | 3.0 | 6897 | 0.7939 | 0.8013 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ashishkumar0154/bert-base-uncased-finetune-kggpu
Base model
google-bert/bert-base-uncased