finetuned-xlm-roberta-large

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

• eval_loss: 0.0952
• eval_precision: 0.9310
• eval_recall: 0.9398
• eval_f1: 0.9354
• eval_accuracy: 0.9813
• eval_runtime: 91.6462
• eval_samples_per_second: 27.726
• eval_steps_per_second: 0.873
• epoch: 5.0
• step: 2385

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: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 9

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3