---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DEREXP
  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. -->

# DEREXP

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: 3.5797
- Mse: 3.5797
- Mae: 1.4414
- R2: 0.3526
- Accuracy: 0.2268

## 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: 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
| 14.19         | 0.08  | 500  | 4.6174          | 4.6174 | 1.6744 | 0.1649 | 0.198    |
| 4.527         | 0.16  | 1000 | 3.9019          | 3.9019 | 1.5164 | 0.2943 | 0.2192   |
| 4.3036        | 0.24  | 1500 | 5.3501          | 5.3501 | 1.8130 | 0.0324 | 0.1736   |
| 4.0923        | 0.32  | 2000 | 3.8948          | 3.8948 | 1.5150 | 0.2956 | 0.2142   |
| 4.0042        | 0.4   | 2500 | 3.7648          | 3.7648 | 1.4905 | 0.3191 | 0.2162   |
| 3.8685        | 0.48  | 3000 | 3.7741          | 3.7741 | 1.4908 | 0.3174 | 0.2152   |
| 3.8928        | 0.56  | 3500 | 3.7122          | 3.7122 | 1.4738 | 0.3286 | 0.214    |
| 3.8193        | 0.64  | 4000 | 3.7020          | 3.7020 | 1.4727 | 0.3304 | 0.2182   |
| 3.6929        | 0.72  | 4500 | 3.6419          | 3.6419 | 1.4575 | 0.3413 | 0.2266   |
| 3.7974        | 0.8   | 5000 | 3.6995          | 3.6995 | 1.4656 | 0.3309 | 0.2202   |
| 3.7752        | 0.88  | 5500 | 3.6344          | 3.6344 | 1.4559 | 0.3427 | 0.2276   |
| 3.6254        | 0.96  | 6000 | 3.5797          | 3.5797 | 1.4414 | 0.3526 | 0.2268   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1