
<!-- 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. -->

# fine-tuned-ai-ss-hs-01

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- AUC: 0.88609
- Precision: 0.8514
- Accuracy: 0.8101
- F1: 0.7875
- Recall: 0.7326

## 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: 1.1207606211860595e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 357  | 1.0285          | 0.6955   | 0.5657 | 0.8987    | 0.4128 |
| 0.5857        | 2.0   | 714  | 1.0350          | 0.7207   | 0.6296 | 0.8673    | 0.4942 |
| 0.51          | 3.0   | 1071 | 0.7467          | 0.8156   | 0.7975 | 0.8442    | 0.7558 |
| 0.51          | 4.0   | 1428 | 0.8376          | 0.8101   | 0.7875 | 0.8514    | 0.7326 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "fine-tuned-ai-ss-hs-01", "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 

fine-tuned-ai-ss-hs-01
======================


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


* AUC: 0.88609
* Precision: 0.8514
* Accuracy: 0.8101
* F1: 0.7875
* Recall: 0.7326


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: 1.1207606211860595e-05
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.1207606211860595e-05
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* 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: 1.1207606211860595e-05
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Tokenizers 0.12.1
passage: 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: 1.1207606211860595e-05
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Tokenizers 0.12.1