---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ft1500_norm300
  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

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: 1.0940
- Mse: 4.3760
- Mae: 1.4084
- R2: 0.4625
- Accuracy: 0.3517

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
| 0.7424        | 1.0   | 3122  | 1.1071          | 4.4286 | 1.4098 | 0.4561 | 0.3338   |
| 0.5038        | 2.0   | 6244  | 1.1794          | 4.7177 | 1.4140 | 0.4205 | 0.3677   |
| 0.356         | 3.0   | 9366  | 1.0717          | 4.2866 | 1.3852 | 0.4735 | 0.3581   |
| 0.2293        | 4.0   | 12488 | 1.0940          | 4.3760 | 1.4084 | 0.4625 | 0.3517   |


### Framework versions

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