transformers tensorboard safetensors bert multiple-choice generated_from_trainer base_model:bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-swag
  results: []
---

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# bert-base-uncased-finetuned-swag

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1649
- Accuracy: 0.4857

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 26   | 1.3860          | 0.3238   |
| No log        | 2.0   | 52   | 1.3833          | 0.3238   |
| No log        | 3.0   | 78   | 1.3547          | 0.3810   |
| No log        | 4.0   | 104  | 1.3130          | 0.3905   |
| No log        | 5.0   | 130  | 1.3733          | 0.4000   |
| No log        | 6.0   | 156  | 1.6432          | 0.4476   |
| No log        | 7.0   | 182  | 1.8118          | 0.4952   |
| No log        | 8.0   | 208  | 2.0408          | 0.4571   |
| No log        | 9.0   | 234  | 1.9043          | 0.4952   |
| No log        | 10.0  | 260  | 1.9755          | 0.4952   |
| No log        | 11.0  | 286  | 2.0813          | 0.4857   |
| No log        | 12.0  | 312  | 2.0578          | 0.4571   |
| No log        | 13.0  | 338  | 2.0979          | 0.4762   |
| No log        | 14.0  | 364  | 2.1136          | 0.4857   |
| No log        | 15.0  | 390  | 2.1649          | 0.4857   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
