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# final_five_class_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1000
- F1: 0.9566
- Roc Auc: 0.9664
- Accuracy: 0.875

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 250  | 0.2560          | 0.8761 | 0.9004  | 0.665    |
| 0.3126        | 2.0   | 500  | 0.2082          | 0.8966 | 0.9177  | 0.7025   |
| 0.3126        | 3.0   | 750  | 0.1879          | 0.9024 | 0.9254  | 0.705    |
| 0.2165        | 4.0   | 1000 | 0.1654          | 0.9166 | 0.9348  | 0.755    |
| 0.2165        | 5.0   | 1250 | 0.1403          | 0.9346 | 0.9500  | 0.7975   |
| 0.1619        | 6.0   | 1500 | 0.1288          | 0.9394 | 0.9523  | 0.815    |
| 0.1619        | 7.0   | 1750 | 0.1112          | 0.9515 | 0.9614  | 0.855    |
| 0.1161        | 8.0   | 2000 | 0.1112          | 0.9492 | 0.9585  | 0.8575   |
| 0.1161        | 9.0   | 2250 | 0.1029          | 0.9536 | 0.9631  | 0.8725   |
| 0.086         | 10.0  | 2500 | 0.1000          | 0.9566 | 0.9664  | 0.875    |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.1+cpu
- Datasets 2.8.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "final_five_class_classification", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

final\_five\_class\_classification
==================================


This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1000
* F1: 0.9566
* Roc Auc: 0.9664
* Accuracy: 0.875


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: 10


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cpu
* Datasets 2.8.0
* Tokenizers 0.12.1



### 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: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cpu
* Datasets 2.8.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #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: 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: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cpu
* Datasets 2.8.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #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: 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: 10### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cpu
* Datasets 2.8.0
* Tokenizers 0.12.1