results

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

• eval_loss: 0.3651
• eval_label_0_f1: 0.7305
• eval_label_0_accuracy: 0.9498
• eval_label_1_f1: 0.8458
• eval_label_1_accuracy: 0.8573
• eval_label_2_f1: 0.7816
• eval_label_2_accuracy: 0.9576
• eval_label_3_f1: 0.7638
• eval_label_3_accuracy: 0.9097
• eval_label_4_f1: 0.6438
• eval_label_4_accuracy: 0.9420
• eval_label_5_f1: 0.6857
• eval_label_5_accuracy: 0.9755
• eval_runtime: 5.7337
• eval_samples_per_second: 156.444
• eval_steps_per_second: 5.058
• epoch: 5.0
• step: 795

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: 1e-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: 10

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2