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# Regression_longformer

This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- Mse: 0.0973
- Mae: 0.2464
- R2: 0.9498
- Accuracy: 0.8571

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2      | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 4    | 3.1150          | 3.1150 | 1.4245 | -1.9228 | 0.2857   |
| No log        | 2.0   | 8    | 2.4934          | 2.4934 | 1.2570 | -1.3396 | 0.4286   |
| No log        | 3.0   | 12   | 1.5812          | 1.5812 | 1.1308 | -0.4836 | 0.1429   |
| No log        | 4.0   | 16   | 1.4004          | 1.4004 | 1.0230 | -0.3140 | 0.4286   |
| No log        | 5.0   | 20   | 2.4083          | 2.4083 | 1.2028 | -1.2597 | 0.4286   |
| No log        | 6.0   | 24   | 2.4795          | 2.4795 | 1.2186 | -1.3265 | 0.2857   |
| No log        | 7.0   | 28   | 1.9781          | 1.9781 | 1.0441 | -0.8560 | 0.5714   |
| No log        | 8.0   | 32   | 1.6604          | 1.6604 | 0.9238 | -0.5579 | 0.5714   |
| No log        | 9.0   | 36   | 1.5105          | 1.5105 | 0.9193 | -0.4172 | 0.5714   |
| No log        | 10.0  | 40   | 0.9750          | 0.9750 | 0.7766 | 0.0852  | 0.5714   |
| No log        | 11.0  | 44   | 0.6147          | 0.6147 | 0.6262 | 0.4233  | 0.2857   |
| No log        | 12.0  | 48   | 0.5429          | 0.5429 | 0.5941 | 0.4906  | 0.4286   |
| No log        | 13.0  | 52   | 0.4183          | 0.4183 | 0.5999 | 0.6075  | 0.4286   |
| No log        | 14.0  | 56   | 0.5570          | 0.5570 | 0.6746 | 0.4774  | 0.2857   |
| No log        | 15.0  | 60   | 0.2450          | 0.2450 | 0.4159 | 0.7701  | 0.7143   |
| No log        | 16.0  | 64   | 0.1650          | 0.1650 | 0.3241 | 0.8452  | 0.7143   |
| No log        | 17.0  | 68   | 0.1367          | 0.1367 | 0.2701 | 0.8718  | 0.8571   |
| No log        | 18.0  | 72   | 0.1225          | 0.1225 | 0.2905 | 0.8850  | 0.8571   |
| No log        | 19.0  | 76   | 0.1169          | 0.1169 | 0.2825 | 0.8903  | 0.8571   |
| No log        | 20.0  | 80   | 0.1309          | 0.1309 | 0.3046 | 0.8772  | 0.8571   |
| No log        | 21.0  | 84   | 0.4585          | 0.4585 | 0.5426 | 0.5698  | 0.5714   |
| No log        | 22.0  | 88   | 0.2451          | 0.2451 | 0.4216 | 0.7700  | 0.5714   |
| No log        | 23.0  | 92   | 0.1123          | 0.1123 | 0.2678 | 0.8946  | 0.8571   |
| No log        | 24.0  | 96   | 0.0942          | 0.0942 | 0.2816 | 0.9116  | 1.0      |
| No log        | 25.0  | 100  | 0.1239          | 0.1239 | 0.2445 | 0.8838  | 0.8571   |
| No log        | 26.0  | 104  | 0.2268          | 0.2268 | 0.3540 | 0.7872  | 0.8571   |
| No log        | 27.0  | 108  | 0.3575          | 0.3575 | 0.4408 | 0.6645  | 0.5714   |
| No log        | 28.0  | 112  | 0.3418          | 0.3418 | 0.4349 | 0.6793  | 0.5714   |
| No log        | 29.0  | 116  | 0.2677          | 0.2677 | 0.3958 | 0.7488  | 0.5714   |
| No log        | 30.0  | 120  | 0.2235          | 0.2235 | 0.3717 | 0.7903  | 0.5714   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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

Regression\_longformer
======================


This model is a fine-tuned version of allenai/longformer-base-4096 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0973
* Mse: 0.0973
* Mae: 0.2464
* R2: 0.9498
* Accuracy: 0.8571


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.26.1
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #longformer #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #longformer #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2