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# roberta-base-finetuned-sms-spam-detection

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the sms_spam dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0133
- Accuracy: 0.998

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0363        | 1.0   | 250  | 0.0156          | 0.996    |
| 0.0147        | 2.0   | 500  | 0.0133          | 0.998    |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["sms_spam"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-finetuned-sms-spam-detection", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "sms_spam", "type": "sms_spam", "args": "plain_text"}, "metrics": [{"type": "accuracy", "value": 0.998, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard safetensors roberta text-classification generated_from_trainer dataset:sms_spam base_model:roberta-base license:mit model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #dataset-sms_spam #base_model-roberta-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

roberta-base-finetuned-sms-spam-detection
=========================================


This model is a fine-tuned version of roberta-base on the sms\_spam dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0133
* Accuracy: 0.998


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


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


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


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #dataset-sms_spam #base_model-roberta-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


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


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #dataset-sms_spam #base_model-roberta-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


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


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0