roberta-classifier_batch16_3dataset

This model is a fine-tuned version of microsoft/deberta-large-mnli on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.6920
• eval_Accuracy: 0.525
• eval_AUC: 0.498
• eval_runtime: 78.0994
• eval_samples_per_second: 37.004
• eval_steps_per_second: 2.318
• epoch: 3.0
• step: 2169

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.1