deberta-v3-large-ft-icar-a-v0.11-to-b64

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.7272
• eval_accuracy: 0.8998
• eval_precision: 0.8850
• eval_recall: 0.8556
• eval_f1: 0.8677
• eval_runtime: 26.5549
• eval_samples_per_second: 19.921
• eval_steps_per_second: 19.921
• epoch: 31.0
• step: 1023

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-06
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 64
• total_train_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.0+cu126
• Datasets 4.4.2
• Tokenizers 0.22.1