mdeberta-v3-base-finetuned-other-environment-classification-full

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

mdeberta-v3-base-finetuned-other-environment-classification-full

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1516
• Accuracy: 0.9680
• Accuracy Balanced: 0.8964
• F1 Macro: 0.8871
• F1 Weighted: 0.9684
• F1 Micro: 0.9680
• F1 Positive: 0.7915
• Precision Macro: 0.8783
• Precision Weighted: 0.9688
• Recall Macro: 0.8964
• Recall Weighted: 0.9680
• Mcc: 0.7745
• Roc Auc: 0.9819
• Pr Auc: 0.8681

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: 8
• eval_batch_size: 8
• seed: 42
• 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
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1