bert-base-uncased-finetuned-swag
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: 1.0022
- Accuracy: 0.7915
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 |
|---|---|---|---|---|
| 0.7606 | 1.0 | 4597 | 0.6042 | 0.7637 |
| 0.3872 | 2.0 | 9194 | 0.6042 | 0.7875 |
| 0.146 | 3.0 | 13791 | 1.0022 | 0.7915 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Downloads last month
- 21
Inference API (serverless) does not yet support transformers models for this pipeline type.
Model tree for b10401015/bert-base-uncased-finetuned-swag
Base model
google-bert/bert-base-uncased