---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased-swag-full
  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. -->

# bert-large-uncased-swag-full

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co./google-bert/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5367
- Accuracy: 0.8024

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7878        | 1.0   | 4597  | 0.6288          | 0.7612   |
| 0.4475        | 2.0   | 9194  | 0.6195          | 0.7849   |
| 0.215         | 3.0   | 13791 | 0.7408          | 0.7893   |
| 0.0957        | 4.0   | 18388 | 1.3131          | 0.7976   |
| 0.0274        | 5.0   | 22985 | 1.5367          | 0.8024   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1