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# testing_params_cair1

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: 0.0914
- F1: 0.9609
- Roc Auc: 0.9657
- Accuracy: 0.8862

## 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   | 248  | 0.2621          | 0.8898 | 0.9140  | 0.6748   |
| No log        | 2.0   | 496  | 0.2282          | 0.8700 | 0.8909  | 0.6504   |
| 0.3113        | 3.0   | 744  | 0.1869          | 0.9168 | 0.9332  | 0.7561   |
| 0.3113        | 4.0   | 992  | 0.1627          | 0.9247 | 0.9384  | 0.7805   |
| 0.1955        | 5.0   | 1240 | 0.1440          | 0.9316 | 0.9404  | 0.8049   |
| 0.1955        | 6.0   | 1488 | 0.1263          | 0.9455 | 0.9532  | 0.8455   |
| 0.1343        | 7.0   | 1736 | 0.1087          | 0.9478 | 0.9553  | 0.8537   |
| 0.1343        | 8.0   | 1984 | 0.0951          | 0.9567 | 0.9630  | 0.8862   |
| 0.0874        | 9.0   | 2232 | 0.0937          | 0.9609 | 0.9657  | 0.8862   |
| 0.0874        | 10.0  | 2480 | 0.0914          | 0.9609 | 0.9657  | 0.8862   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1+cpu
- Datasets 2.9.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "testing_params_cair1", "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 

testing\_params\_cair1
======================


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: 0.0914
* F1: 0.9609
* Roc Auc: 0.9657
* Accuracy: 0.8862


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 4.26.1
* Pytorch 1.12.1+cpu
* Datasets 2.9.0
* 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 4.26.1
* Pytorch 1.12.1+cpu
* Datasets 2.9.0
* 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 4.26.1
* Pytorch 1.12.1+cpu
* Datasets 2.9.0
* 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 4.26.1
* Pytorch 1.12.1+cpu
* Datasets 2.9.0
* Tokenizers 0.12.1