---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-petco-text_content-ctr
  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. -->

# bert-petco-text_content-ctr

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0034
- Mse: 0.0034
- Rmse: 0.0586
- Mae: 0.0408
- R2: 0.4036
- Accuracy: 0.6833

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Rmse   | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:--------:|
| 0.0239        | 1.0   | 15   | 0.0049          | 0.0049 | 0.0701 | 0.0519 | 0.1473 | 0.5833   |
| 0.0095        | 2.0   | 30   | 0.0047          | 0.0047 | 0.0688 | 0.0537 | 0.1774 | 0.5667   |
| 0.0071        | 3.0   | 45   | 0.0057          | 0.0057 | 0.0756 | 0.0643 | 0.0065 | 0.4      |
| 0.0062        | 4.0   | 60   | 0.0046          | 0.0046 | 0.0675 | 0.0544 | 0.2089 | 0.5      |
| 0.0058        | 5.0   | 75   | 0.0048          | 0.0048 | 0.0692 | 0.0495 | 0.1682 | 0.6833   |
| 0.0048        | 6.0   | 90   | 0.0046          | 0.0046 | 0.0678 | 0.0543 | 0.2014 | 0.5      |
| 0.0042        | 7.0   | 105  | 0.0039          | 0.0039 | 0.0621 | 0.0465 | 0.3295 | 0.6833   |
| 0.0034        | 8.0   | 120  | 0.0038          | 0.0038 | 0.0617 | 0.0444 | 0.3382 | 0.6667   |
| 0.0031        | 9.0   | 135  | 0.0040          | 0.0040 | 0.0630 | 0.0462 | 0.3106 | 0.6667   |
| 0.0037        | 10.0  | 150  | 0.0040          | 0.0040 | 0.0629 | 0.0439 | 0.3140 | 0.7167   |
| 0.0028        | 11.0  | 165  | 0.0041          | 0.0041 | 0.0638 | 0.0439 | 0.2942 | 0.6833   |
| 0.0027        | 12.0  | 180  | 0.0041          | 0.0041 | 0.0642 | 0.0447 | 0.2854 | 0.7167   |
| 0.0026        | 13.0  | 195  | 0.0036          | 0.0036 | 0.0598 | 0.0422 | 0.3788 | 0.7      |
| 0.0025        | 14.0  | 210  | 0.0034          | 0.0034 | 0.0587 | 0.0420 | 0.4021 | 0.6833   |
| 0.002         | 15.0  | 225  | 0.0034          | 0.0034 | 0.0586 | 0.0408 | 0.4036 | 0.6833   |
| 0.0022        | 16.0  | 240  | 0.0037          | 0.0037 | 0.0607 | 0.0420 | 0.3610 | 0.7      |
| 0.0019        | 17.0  | 255  | 0.0037          | 0.0037 | 0.0607 | 0.0416 | 0.3595 | 0.7167   |
| 0.0018        | 18.0  | 270  | 0.0037          | 0.0037 | 0.0612 | 0.0423 | 0.3493 | 0.6833   |
| 0.0018        | 19.0  | 285  | 0.0036          | 0.0036 | 0.0597 | 0.0409 | 0.3804 | 0.7167   |
| 0.0019        | 20.0  | 300  | 0.0035          | 0.0035 | 0.0589 | 0.0407 | 0.3967 | 0.6667   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2