---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-petco-fullemailbody-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-fullemailbody-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: 0.0024
- Mse: 0.0024
- Rmse: 0.0487
- Mae: 0.0369
- R2: 0.3917

## 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: 1e-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      |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| 0.0259        | 1.0   | 15   | 0.0045          | 0.0045 | 0.0671 | 0.0558 | -0.1551 |
| 0.0131        | 2.0   | 30   | 0.0042          | 0.0042 | 0.0645 | 0.0501 | -0.0669 |
| 0.0114        | 3.0   | 45   | 0.0037          | 0.0037 | 0.0609 | 0.0514 | 0.0488  |
| 0.0118        | 4.0   | 60   | 0.0033          | 0.0033 | 0.0576 | 0.0446 | 0.1471  |
| 0.0097        | 5.0   | 75   | 0.0036          | 0.0036 | 0.0599 | 0.0460 | 0.0790  |
| 0.0095        | 6.0   | 90   | 0.0037          | 0.0037 | 0.0606 | 0.0462 | 0.0568  |
| 0.0086        | 7.0   | 105  | 0.0040          | 0.0040 | 0.0629 | 0.0485 | -0.0177 |
| 0.0083        | 8.0   | 120  | 0.0026          | 0.0026 | 0.0513 | 0.0392 | 0.3232  |
| 0.0077        | 9.0   | 135  | 0.0035          | 0.0035 | 0.0595 | 0.0445 | 0.0915  |
| 0.0067        | 10.0  | 150  | 0.0037          | 0.0037 | 0.0606 | 0.0462 | 0.0561  |
| 0.0066        | 11.0  | 165  | 0.0025          | 0.0025 | 0.0503 | 0.0394 | 0.3499  |
| 0.0066        | 12.0  | 180  | 0.0034          | 0.0034 | 0.0580 | 0.0475 | 0.1355  |
| 0.0046        | 13.0  | 195  | 0.0024          | 0.0024 | 0.0487 | 0.0369 | 0.3917  |
| 0.0052        | 14.0  | 210  | 0.0035          | 0.0035 | 0.0587 | 0.0454 | 0.1137  |
| 0.0049        | 15.0  | 225  | 0.0032          | 0.0032 | 0.0567 | 0.0438 | 0.1753  |
| 0.0041        | 16.0  | 240  | 0.0034          | 0.0034 | 0.0581 | 0.0445 | 0.1321  |
| 0.0039        | 17.0  | 255  | 0.0030          | 0.0030 | 0.0548 | 0.0412 | 0.2277  |
| 0.0042        | 18.0  | 270  | 0.0036          | 0.0036 | 0.0603 | 0.0465 | 0.0676  |
| 0.0035        | 19.0  | 285  | 0.0036          | 0.0036 | 0.0601 | 0.0461 | 0.0719  |
| 0.0031        | 20.0  | 300  | 0.0033          | 0.0033 | 0.0574 | 0.0435 | 0.1548  |


### Framework versions

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