---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
widget:
- text: people buying sweets at the market. [SEP] saint nicholas festival market
  example_title: Caption vs Title
base_model: distilbert-base-uncased
model-index:
- name: Heritage-in-the-Digital-Age-expression-comparison
  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. -->

# Heritage-in-the-Digital-Age-expression-comparison

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5281
- Accuracy: 0.7709

## 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: 2e-05
- train_batch_size: 15
- eval_batch_size: 15
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 136  | 0.5281          | 0.7709   |
| No log        | 2.0   | 272  | 0.5288          | 0.7709   |
| No log        | 3.0   | 408  | 0.5311          | 0.7629   |
| 0.4623        | 4.0   | 544  | 0.5814          | 0.7595   |
| 0.4623        | 5.0   | 680  | 0.5764          | 0.7549   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2