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# bert-base-uncased-finetuned-sdg-Mar23

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: 0.3234
- Acc: 0.9113

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

##Labelling
0:'1', 1:'10', 2:'11', 3:'12', 4:'13', 5:'14', 6:'15', 7:'16', 8:'2', 9:'3', 10:'4', 11:'5', 12:'6', 13:'7', 14:'8', 15:'9'


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4165        | 1.0   | 1098 | 0.3656          | 0.8908 |
| 0.2062        | 2.0   | 2196 | 0.3234          | 0.9113 |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.12.0a0+8a1a93a
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-finetuned-sdg-Mar23", "results": []}]}
transformers pytorch safetensors bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

bert-base-uncased-finetuned-sdg-Mar23
=====================================


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: 0.3234
* Acc: 0.9113


Model description
-----------------


More information needed


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


More information needed


##Labelling
0:'1', 1:'10', 2:'11', 3:'12', 4:'13', 5:'14', 6:'15', 7:'16', 8:'2', 9:'3', 10:'4', 11:'5', 12:'6', 13:'7', 14:'8', 15:'9'


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 1.12.0a0+8a1a93a
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.12.0a0+8a1a93a
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.12.0a0+8a1a93a
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 1.12.0a0+8a1a93a
* Datasets 2.10.1
* Tokenizers 0.13.2