iw-conspir-v2

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iw-conspir-v2

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

• Loss: 1.2794
• F1 Contradictory: 0.0
• F1 Overriding Suspicion: 0.7358
• F1 Nefarious Intent: 0.6667
• F1 Persecuted Victim: 0.2727
• F1 Immune To Evidence: 0.3390
• F1 Reinterpreting Randomness: 0.3889
• Macro F1: 0.4005
• Micro F1: 0.5789

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: 32
• 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_steps: 0.1
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2