---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ft1500_norm300_aug5_10_8x
  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_norm300_aug5_10_8x

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: 1.0667
- Mse: 4.2666
- Mae: 1.3594
- R2: 0.4759
- Accuracy: 0.3619

## 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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
| 0.839         | 1.0   | 6364  | 1.0965          | 4.3859 | 1.5243 | 0.4613 | 0.2012   |
| 0.4412        | 2.0   | 12728 | 0.9976          | 3.9905 | 1.4462 | 0.5099 | 0.2473   |
| 0.2543        | 3.0   | 19092 | 1.0667          | 4.2666 | 1.3594 | 0.4759 | 0.3619   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1