deberta-final

This model is a fine-tuned version of microsoft/deberta-large on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.4335
• eval_accuracy: 0.8762
• eval_f1: 0.8762
• eval_runtime: 1227.0064
• eval_samples_per_second: 85.273
• eval_steps_per_second: 2.843
• epoch: 2.6816
• step: 26500

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: 3e-05
• train_batch_size: 30
• eval_batch_size: 30
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 60
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 600
• num_epochs: 7
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0
• Datasets 3.0.0
• Tokenizers 0.19.1