---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: arg-quality-regression
  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. -->

# arg-quality-regression

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0342
- Mse: 0.0342
- Mae: 0.1359
- R2: 0.1353
- Accuracy: 0.9808

## 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: 11

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2      | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------:|:--------:|
| 0.0277        | 1.0   | 1512  | 0.0398          | 0.0398 | 0.1450 | -0.0046 | 0.9736   |
| 0.0218        | 2.0   | 3024  | 0.0342          | 0.0342 | 0.1359 | 0.1353  | 0.9808   |
| 0.0169        | 3.0   | 4536  | 0.0367          | 0.0367 | 0.1409 | 0.0717  | 0.9783   |
| 0.0114        | 4.0   | 6048  | 0.0400          | 0.0400 | 0.1477 | -0.0108 | 0.9751   |
| 0.0075        | 5.0   | 7560  | 0.0439          | 0.0439 | 0.1564 | -0.1093 | 0.9704   |
| 0.006         | 6.0   | 9072  | 0.0465          | 0.0465 | 0.1626 | -0.1749 | 0.9661   |
| 0.0051        | 7.0   | 10584 | 0.0429          | 0.0429 | 0.1574 | -0.0851 | 0.9729   |
| 0.0037        | 8.0   | 12096 | 0.0440          | 0.0440 | 0.1590 | -0.1123 | 0.9720   |
| 0.0035        | 9.0   | 13608 | 0.0412          | 0.0412 | 0.1534 | -0.0401 | 0.9755   |
| 0.0029        | 10.0  | 15120 | 0.0415          | 0.0415 | 0.1537 | -0.0487 | 0.9743   |
| 0.0028        | 11.0  | 16632 | 0.0438          | 0.0438 | 0.1589 | -0.1080 | 0.9712   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1