xlm-roberta-base-language-detection-disaster-twitter

This model is a fine-tuned version of papluca/xlm-roberta-base-language-detection on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4869
• F1: 0.7902

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	381	0.4407	0.7701
0.4972	2.0	762	0.4186	0.7560
0.3742	3.0	1143	0.4869	0.7902

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.2+cpu
• Datasets 2.1.0
• Tokenizers 0.15.2