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# Regression_distilbert-base-uncased

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1187
- Mse: 2.1187
- Mae: 1.3097
- R2: -0.0932
- Accuracy: 0.1429

## 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: 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2      | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 2    | 3.3933          | 3.3933 | 1.5228 | -2.1839 | 0.2857   |
| No log        | 2.0   | 4    | 3.0571          | 3.0571 | 1.4011 | -1.8684 | 0.4286   |
| No log        | 3.0   | 6    | 2.6747          | 2.6747 | 1.2786 | -1.5096 | 0.4286   |
| No log        | 4.0   | 8    | 2.3024          | 2.3024 | 1.2088 | -1.1603 | 0.4286   |
| No log        | 5.0   | 10   | 1.9496          | 1.9496 | 1.1459 | -0.8292 | 0.4286   |
| No log        | 6.0   | 12   | 1.6637          | 1.6637 | 1.1225 | -0.5610 | 0.2857   |
| No log        | 7.0   | 14   | 1.4167          | 1.4167 | 1.0938 | -0.3293 | 0.1429   |
| No log        | 8.0   | 16   | 1.2365          | 1.2365 | 1.0609 | -0.1602 | 0.0      |
| No log        | 9.0   | 18   | 1.1239          | 1.1239 | 1.0234 | -0.0545 | 0.0      |
| No log        | 10.0  | 20   | 1.0879          | 1.0879 | 0.9906 | -0.0207 | 0.0      |
| No log        | 11.0  | 22   | 1.1122          | 1.1122 | 0.9599 | -0.0436 | 0.2857   |
| No log        | 12.0  | 24   | 1.1879          | 1.1879 | 0.9374 | -0.1145 | 0.2857   |
| No log        | 13.0  | 26   | 1.2784          | 1.2784 | 0.9132 | -0.1995 | 0.4286   |
| No log        | 14.0  | 28   | 1.3756          | 1.3756 | 0.8905 | -0.2907 | 0.4286   |
| No log        | 15.0  | 30   | 1.4710          | 1.4710 | 0.9093 | -0.3802 | 0.4286   |
| No log        | 16.0  | 32   | 1.5513          | 1.5513 | 0.9333 | -0.4555 | 0.4286   |
| No log        | 17.0  | 34   | 1.6094          | 1.6094 | 0.9491 | -0.5101 | 0.5714   |
| No log        | 18.0  | 36   | 1.6446          | 1.6446 | 0.9567 | -0.5431 | 0.5714   |
| No log        | 19.0  | 38   | 1.6510          | 1.6510 | 0.9555 | -0.5491 | 0.5714   |
| No log        | 20.0  | 40   | 1.6425          | 1.6425 | 0.9503 | -0.5412 | 0.5714   |
| No log        | 21.0  | 42   | 1.6254          | 1.6254 | 0.9455 | -0.5251 | 0.5714   |
| No log        | 22.0  | 44   | 1.6025          | 1.6025 | 0.9378 | -0.5036 | 0.5714   |
| No log        | 23.0  | 46   | 1.5758          | 1.5758 | 0.9289 | -0.4786 | 0.5714   |
| No log        | 24.0  | 48   | 1.5583          | 1.5583 | 0.9233 | -0.4622 | 0.5714   |
| No log        | 25.0  | 50   | 1.5504          | 1.5504 | 0.9210 | -0.4547 | 0.5714   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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

Regression\_distilbert-base-uncased
===================================


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


* Loss: 2.1187
* Mse: 2.1187
* Mae: 1.3097
* R2: -0.0932
* Accuracy: 0.1429


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: 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: 25


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 25 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 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: 25 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 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: 25### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2