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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased-swag
results: []
datasets:
- allenai/swag
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fine-tuned-bert-base-uncased-swag
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on SWAG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5259
- Accuracy: 0.8134
## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7736 | 1.0 | 1150 | 0.5534 | 0.7911 |
| 0.5913 | 2.0 | 2300 | 0.5009 | 0.8086 |
| 0.4462 | 3.0 | 3450 | 0.5014 | 0.8122 |
| 0.3695 | 4.0 | 4600 | 0.5259 | 0.8134 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |