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# roberta-large-finetuned-disaster

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the [Disaster Tweets](https://www.kaggle.com/competitions/nlp-getting-started/data).
It achieves the following results on the evaluation set:
- Loss: 0.3668
- Accuracy: 0.8399
- F1: 0.8396

## Model description
The model is a fine-tuned version on the disaster dataset on Kaggle. You can enter the following statement to see if the label changes:
```txt
Forest fire near La Ronge Sask. Canada

Just happened a terrible car crash

What's up man?

Summer is lovely
```


## 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: 32
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.446         | 1.0   | 226  | 0.3657          | 0.8583   | 0.8580 |
| 0.3295        | 2.0   | 452  | 0.3668          | 0.8399   | 0.8396 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "widget": [{"text": "Forest fire near La Ronge Sask. Canada", "example_title": "\u6709\u707e\u60c5"}, {"text": "Summer is lovely", "example_title": "\u65e0\u707e\u60c5"}], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-finetuned-disaster", "results": []}]}
transformers pytorch safetensors roberta text-classification generated_from_trainer en base_model:roberta-large license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #generated_from_trainer #en #base_model-roberta-large #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-large-finetuned-disaster
================================


This model is a fine-tuned version of roberta-large on the Disaster Tweets.
It achieves the following results on the evaluation set:


* Loss: 0.3668
* Accuracy: 0.8399
* F1: 0.8396


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


The model is a fine-tuned version on the disaster dataset on Kaggle. You can enter the following statement to see if the label changes:


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: 32
* eval\_batch\_size: 32
* 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 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #generated_from_trainer #en #base_model-roberta-large #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #generated_from_trainer #en #base_model-roberta-large #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2