---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ft1500_reg3
  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_reg3

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: 0.7954
- Mse: 0.7954
- Mae: 0.6900
- R2: 0.4769
- Accuracy: 0.4459

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
| 1.018         | 1.0   | 3122  | 0.7491          | 0.7491 | 0.6739 | 0.5073 | 0.4555   |
| 0.668         | 2.0   | 6244  | 0.7397          | 0.7397 | 0.6687 | 0.5135 | 0.4689   |
| 0.4871        | 3.0   | 9366  | 0.7542          | 0.7542 | 0.6730 | 0.5040 | 0.4606   |
| 0.3419        | 4.0   | 12488 | 0.7710          | 0.7710 | 0.6802 | 0.4929 | 0.4536   |
| 0.2532        | 5.0   | 15610 | 0.7954          | 0.7954 | 0.6900 | 0.4769 | 0.4459   |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1