results

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: 1.9243
• eval_accuracy: 0.1677
• eval_f1: 0.0482
• eval_precision: 0.0281
• eval_recall: 0.1677
• eval_runtime: 27.8461
• eval_samples_per_second: 41.334
• eval_steps_per_second: 10.343
• epoch: 2.0
• step: 3064

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1