metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- swag
metrics:
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased-swag
results: []
fine-tuned-bert-base-uncased-swag
This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.7481
- Accuracy: 0.8095
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: 1.5e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7255 | 1.0 | 4597 | 0.5368 | 0.7954 |
| 0.4771 | 2.0 | 9194 | 0.5097 | 0.8066 |
| 0.2964 | 3.0 | 13791 | 0.6103 | 0.8062 |
| 0.2029 | 4.0 | 18388 | 0.7481 | 0.8095 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.11.0
- Datasets 2.19.1
- Tokenizers 0.19.1