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# 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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "Regression_xlnet_NOaug_MSEloss", "results": []}]}
transformers pytorch tensorboard xlnet text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlnet #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

Regression\_xlnet\_NOaug\_MSEloss
=================================


This model is a fine-tuned version of 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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #xlnet #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


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