metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-swag
results: []
bert-base-uncased-finetuned-swag
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3225
- Accuracy: 0.7750
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.6562 | 1.0 | 4597 | 0.6126 | 0.7651 |
| 0.2734 | 2.0 | 9194 | 0.7739 | 0.7702 |
| 0.0846 | 3.0 | 13791 | 1.3225 | 0.7750 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0