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# distilroberta-base-finetuned-suicide-depression

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6622
- Accuracy: 0.7158

## Model description

Just a **POC** of a Transformer fine-tuned on [SDCNL](https://github.com/ayaanzhaque/SDCNL) dataset for suicide (label 1) or depression (label 0) detection in tweets.
**DO NOT use it in production**

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 214  | 0.6204          | 0.6632   |
| No log        | 2.0   | 428  | 0.6622          | 0.7158   |
| 0.5244        | 3.0   | 642  | 0.7312          | 0.6684   |
| 0.5244        | 4.0   | 856  | 0.9711          | 0.7105   |
| 0.2876        | 5.0   | 1070 | 1.1620          | 0.7      |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.13.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "widget": [{"text": "It's in the back of my mind. I'm not sure I'll be ok. Not sure I can deal with this. I'll try...I will try. Even though it's hard to see the point. But...this still isn't off the table."}], "model-index": [{"name": "distilroberta-base-finetuned-suicide-depression", "results": []}]}
transformers pytorch tensorboard safetensors roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilroberta-base-finetuned-suicide-depression
===============================================


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


* Loss: 0.6622
* Accuracy: 0.7158


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


Just a POC of a Transformer fine-tuned on SDCNL dataset for suicide (label 1) or depression (label 0) detection in tweets.
DO NOT use it in production


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: 5


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3



### 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: 5 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #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: 5 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #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: 5### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3