---
base_model: Liberty-L/swag_pretrained
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Multiple_Choice_swag_lr
  results: []
---

<!-- 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. -->

# Multiple_Choice_swag_lr

This model is a fine-tuned version of [Liberty-L/swag_pretrained](https://huggingface.co/Liberty-L/swag_pretrained) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6283
- Accuracy: 0.6483

## 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: 7e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1115        | 1.0   | 1271 | 1.0120          | 0.5954   |
| 0.7999        | 2.0   | 2542 | 1.0345          | 0.6267   |
| 0.4649        | 3.0   | 3813 | 1.2207          | 0.6428   |
| 0.2354        | 4.0   | 5084 | 1.6283          | 0.6483   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0