---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
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: 0.0025
- Mse: 0.0025
- Rmse: 0.0495
- Mae: 0.0390
- R2: 0.3696

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| 0.0347        | 1.0   | 15   | 0.0036          | 0.0036 | 0.0600 | 0.0494 | 0.0749  |
| 0.014         | 2.0   | 30   | 0.0043          | 0.0043 | 0.0656 | 0.0551 | -0.1067 |
| 0.0097        | 3.0   | 45   | 0.0044          | 0.0044 | 0.0662 | 0.0545 | -0.1272 |
| 0.0071        | 4.0   | 60   | 0.0029          | 0.0029 | 0.0540 | 0.0440 | 0.2523  |
| 0.0079        | 5.0   | 75   | 0.0037          | 0.0037 | 0.0611 | 0.0504 | 0.0408  |
| 0.0065        | 6.0   | 90   | 0.0031          | 0.0031 | 0.0558 | 0.0427 | 0.1999  |
| 0.0063        | 7.0   | 105  | 0.0041          | 0.0041 | 0.0637 | 0.0541 | -0.0410 |
| 0.0053        | 8.0   | 120  | 0.0025          | 0.0025 | 0.0499 | 0.0397 | 0.3606  |
| 0.0033        | 9.0   | 135  | 0.0032          | 0.0032 | 0.0563 | 0.0461 | 0.1855  |
| 0.0041        | 10.0  | 150  | 0.0035          | 0.0035 | 0.0590 | 0.0487 | 0.1061  |
| 0.0039        | 11.0  | 165  | 0.0025          | 0.0025 | 0.0495 | 0.0390 | 0.3696  |
| 0.0031        | 12.0  | 180  | 0.0032          | 0.0032 | 0.0568 | 0.0471 | 0.1712  |
| 0.0027        | 13.0  | 195  | 0.0028          | 0.0028 | 0.0533 | 0.0441 | 0.2694  |
| 0.0029        | 14.0  | 210  | 0.0026          | 0.0026 | 0.0511 | 0.0405 | 0.3301  |
| 0.0022        | 15.0  | 225  | 0.0026          | 0.0026 | 0.0507 | 0.0408 | 0.3401  |
| 0.0017        | 16.0  | 240  | 0.0025          | 0.0025 | 0.0498 | 0.0398 | 0.3634  |
| 0.0023        | 17.0  | 255  | 0.0027          | 0.0027 | 0.0518 | 0.0423 | 0.3095  |
| 0.0023        | 18.0  | 270  | 0.0026          | 0.0026 | 0.0513 | 0.0415 | 0.3247  |
| 0.0022        | 19.0  | 285  | 0.0027          | 0.0027 | 0.0523 | 0.0430 | 0.2975  |
| 0.0019        | 20.0  | 300  | 0.0030          | 0.0030 | 0.0551 | 0.0457 | 0.2205  |


### Framework versions

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