---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Regression_xlnet_NOaug_MSEloss
  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. -->

# Regression_xlnet_NOaug_MSEloss

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6460
- Mse: 0.6460
- Mae: 0.7041
- R2: -0.1893
- Accuracy: 0.2632

## 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-12
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2      | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 33   | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 2.0   | 66   | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 3.0   | 99   | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 4.0   | 132  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 5.0   | 165  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 6.0   | 198  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 7.0   | 231  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 8.0   | 264  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 9.0   | 297  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 10.0  | 330  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 11.0  | 363  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 12.0  | 396  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 13.0  | 429  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 14.0  | 462  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |
| No log        | 15.0  | 495  | 0.7342          | 0.7342 | 0.7706 | -1.1938 | 0.2703   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3