---
license: mit
base_model: FacebookAI/roberta-base
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 [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4048
- Mse: 0.4048
- Rmse: 0.6363
- Mae: 0.4301
- R2: 0.2106

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| 1.3784        | 1.0   | 15   | 0.5080          | 0.5080 | 0.7127 | 0.5575 | 0.0095  |
| 0.5017        | 2.0   | 30   | 0.5043          | 0.5043 | 0.7101 | 0.5241 | 0.0166  |
| 0.4986        | 3.0   | 45   | 0.4864          | 0.4864 | 0.6974 | 0.5219 | 0.0515  |
| 0.4621        | 4.0   | 60   | 0.5096          | 0.5096 | 0.7139 | 0.5096 | 0.0063  |
| 0.4483        | 5.0   | 75   | 0.5069          | 0.5069 | 0.7120 | 0.5031 | 0.0116  |
| 0.4396        | 6.0   | 90   | 0.4707          | 0.4707 | 0.6861 | 0.5275 | 0.0822  |
| 0.4145        | 7.0   | 105  | 0.4661          | 0.4661 | 0.6828 | 0.4802 | 0.0910  |
| 0.4293        | 8.0   | 120  | 0.5122          | 0.5122 | 0.7157 | 0.4884 | 0.0012  |
| 0.3681        | 9.0   | 135  | 0.4358          | 0.4358 | 0.6601 | 0.4947 | 0.1502  |
| 0.3349        | 10.0  | 150  | 0.4676          | 0.4676 | 0.6838 | 0.4434 | 0.0882  |
| 0.3003        | 11.0  | 165  | 0.4601          | 0.4601 | 0.6783 | 0.4904 | 0.1028  |
| 0.3132        | 12.0  | 180  | 0.5026          | 0.5026 | 0.7089 | 0.4734 | 0.0200  |
| 0.3446        | 13.0  | 195  | 0.4411          | 0.4411 | 0.6641 | 0.4655 | 0.1399  |
| 0.2935        | 14.0  | 210  | 0.5986          | 0.5986 | 0.7737 | 0.6535 | -0.1672 |
| 0.2301        | 15.0  | 225  | 0.4409          | 0.4409 | 0.6640 | 0.4506 | 0.1403  |
| 0.2152        | 16.0  | 240  | 0.4048          | 0.4048 | 0.6363 | 0.4301 | 0.2106  |
| 0.2056        | 17.0  | 255  | 0.4115          | 0.4115 | 0.6415 | 0.4429 | 0.1976  |
| 0.1885        | 18.0  | 270  | 0.4058          | 0.4058 | 0.6370 | 0.4467 | 0.2087  |
| 0.1754        | 19.0  | 285  | 0.4282          | 0.4282 | 0.6543 | 0.4765 | 0.1651  |
| 0.1758        | 20.0  | 300  | 0.4076          | 0.4076 | 0.6384 | 0.4487 | 0.2052  |


### Framework versions

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