---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ft1500_norm500_aug1
  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. -->

# distilbert-base-uncased-finetuned-ft1500_norm500_aug1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9086
- Mse: 3.6357
- Mae: 1.0762
- R2: 0.2894
- Accuracy: 0.5170

## 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: 4
- eval_batch_size: 4
- 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 | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
| 1.5856        | 1.0   | 5847  | 3.3101          | 4.1376 | 1.1447 | 0.1913 | 0.4965   |
| 0.442         | 2.0   | 11694 | 2.7448          | 3.4311 | 1.0934 | 0.3294 | 0.4523   |
| 0.2703        | 3.0   | 17541 | 2.9300          | 3.6625 | 1.0907 | 0.2841 | 0.4933   |
| 0.1699        | 4.0   | 23388 | 2.7979          | 3.4973 | 1.0808 | 0.3164 | 0.4805   |
| 0.1168        | 5.0   | 29235 | 2.9086          | 3.6357 | 1.0762 | 0.2894 | 0.5170   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1