vp-xlmr-base-dsc

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

• eval_loss: 0.4589
• eval_accuracy: 0.8317
• eval_f1: 0.8313
• eval_precision: 0.8337
• eval_recall: 0.8317
• eval_runtime: 105.9688
• eval_samples_per_second: 51.468
• eval_steps_per_second: 6.436
• epoch: 1.8868
• step: 3000

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1