---
license: apache-2.0
base_model: yimiwang/bert-petco-emailbody-ctr
tags:
- generated_from_trainer
model-index:
- name: roberta-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. -->

# roberta-petco-fullemailbody-ctr

This model is a fine-tuned version of [yimiwang/bert-petco-emailbody-ctr](https://huggingface.co/yimiwang/bert-petco-emailbody-ctr) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0032
- Mse: 0.0032
- Rmse: 0.0568
- Mae: 0.0421
- R2: 0.3701

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|
| 0.0073        | 1.0   | 15   | 0.0044          | 0.0044 | 0.0660 | 0.0490 | 0.1516 |
| 0.0064        | 2.0   | 30   | 0.0042          | 0.0042 | 0.0647 | 0.0511 | 0.1826 |
| 0.0056        | 3.0   | 45   | 0.0046          | 0.0046 | 0.0681 | 0.0497 | 0.0951 |
| 0.0041        | 4.0   | 60   | 0.0037          | 0.0037 | 0.0611 | 0.0452 | 0.2723 |
| 0.0043        | 5.0   | 75   | 0.0039          | 0.0039 | 0.0625 | 0.0460 | 0.2390 |
| 0.0034        | 6.0   | 90   | 0.0035          | 0.0035 | 0.0592 | 0.0449 | 0.3155 |
| 0.0031        | 7.0   | 105  | 0.0036          | 0.0036 | 0.0597 | 0.0476 | 0.3040 |
| 0.003         | 8.0   | 120  | 0.0035          | 0.0035 | 0.0588 | 0.0470 | 0.3255 |
| 0.0029        | 9.0   | 135  | 0.0038          | 0.0038 | 0.0617 | 0.0452 | 0.2582 |
| 0.0023        | 10.0  | 150  | 0.0037          | 0.0037 | 0.0609 | 0.0469 | 0.2767 |
| 0.0023        | 11.0  | 165  | 0.0035          | 0.0035 | 0.0593 | 0.0444 | 0.3135 |
| 0.0021        | 12.0  | 180  | 0.0040          | 0.0040 | 0.0633 | 0.0467 | 0.2179 |
| 0.0024        | 13.0  | 195  | 0.0034          | 0.0034 | 0.0585 | 0.0449 | 0.3327 |
| 0.0024        | 14.0  | 210  | 0.0033          | 0.0033 | 0.0572 | 0.0434 | 0.3620 |
| 0.002         | 15.0  | 225  | 0.0032          | 0.0032 | 0.0568 | 0.0421 | 0.3701 |
| 0.0019        | 16.0  | 240  | 0.0034          | 0.0034 | 0.0581 | 0.0426 | 0.3425 |
| 0.002         | 17.0  | 255  | 0.0035          | 0.0035 | 0.0594 | 0.0439 | 0.3123 |
| 0.0016        | 18.0  | 270  | 0.0033          | 0.0033 | 0.0573 | 0.0426 | 0.3609 |
| 0.0018        | 19.0  | 285  | 0.0033          | 0.0033 | 0.0573 | 0.0424 | 0.3603 |
| 0.0017        | 20.0  | 300  | 0.0032          | 0.0032 | 0.0570 | 0.0423 | 0.3674 |


### Framework versions

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