
<!-- 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_albert_NOaug_MSEloss

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4715
- Mse: 0.4715
- Mae: 0.6001
- R2: 0.1320
- Accuracy: 0.4737

## 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: 2e-05
- 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   | 0.2966          | 0.2966 | 0.4630 | 0.1139  | 0.7568   |
| No log        | 2.0   | 66   | 0.2679          | 0.2679 | 0.4039 | 0.1995  | 0.7568   |
| No log        | 3.0   | 99   | 0.4088          | 0.4088 | 0.5125 | -0.2213 | 0.5405   |
| No log        | 4.0   | 132  | 0.4331          | 0.4331 | 0.5399 | -0.2939 | 0.4865   |
| No log        | 5.0   | 165  | 0.3699          | 0.3699 | 0.4317 | -0.1053 | 0.6757   |
| No log        | 6.0   | 198  | 0.3456          | 0.3456 | 0.4117 | -0.0325 | 0.6216   |
| No log        | 7.0   | 231  | 0.3371          | 0.3371 | 0.4155 | -0.0072 | 0.6757   |
| No log        | 8.0   | 264  | 0.3261          | 0.3261 | 0.3811 | 0.0256  | 0.7297   |
| No log        | 9.0   | 297  | 0.2312          | 0.2312 | 0.2705 | 0.3092  | 0.8108   |
| No log        | 10.0  | 330  | 0.3194          | 0.3194 | 0.3681 | 0.0457  | 0.6757   |
| No log        | 11.0  | 363  | 0.3638          | 0.3638 | 0.4124 | -0.0870 | 0.6757   |
| No log        | 12.0  | 396  | 0.3101          | 0.3101 | 0.3630 | 0.0734  | 0.7027   |
| No log        | 13.0  | 429  | 0.2762          | 0.2762 | 0.3221 | 0.1748  | 0.7568   |
| No log        | 14.0  | 462  | 0.2970          | 0.2970 | 0.3376 | 0.1126  | 0.7297   |
| No log        | 15.0  | 495  | 0.3185          | 0.3185 | 0.3532 | 0.0483  | 0.7297   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "Regression_albert_NOaug_MSEloss", "results": []}]}
transformers pytorch tensorboard albert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #albert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Regression\_albert\_NOaug\_MSEloss
==================================


This model is a fine-tuned version of albert-base-v2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4715
* Mse: 0.4715
* Mae: 0.6001
* R2: 0.1320
* Accuracy: 0.4737


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: 2e-05
* 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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #albert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3