metadata

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: []

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:

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