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# my_awesome_swag_model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7610
- Accuracy: 0.8036

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7503        | 1.0   | 2299 | 0.5744          | 0.7778   |
| 0.3812        | 2.0   | 4598 | 0.5926          | 0.7969   |
| 0.1457        | 3.0   | 6897 | 0.7610          | 0.8036   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["swag"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "my_awesome_swag_model", "results": []}]}
transformers tensorboard safetensors bert multiple-choice generated_from_trainer dataset:swag base_model:bert-base-uncased license:apache-2.0 endpoints_compatible region:us