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---
language:
- en
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
widget:
- text: Forest fire near La Ronge Sask. Canada
example_title: 有灾情
- text: Summer is lovely
example_title: 无灾情
base_model: roberta-large
model-index:
- name: roberta-large-finetuned-disaster
results: []
---
<!-- 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. -->
# 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 |