Tonic/climate-guard-toxic-agent

Climate Guard Toxic Agent - ModernBERT Classifier for Climate Disinformation

This model is a fine-tuned version of answerdotai/ModernBERT-base on the Tonic/climate-guard-toxic-agent dataset. It achieves the following results on the evaluation set:

• Loss: 4.9405
• Accuracy: 0.4774
• F1: 0.4600
• Precision: 0.6228
• Recall: 0.4774
• F1 0 Not Relevant: 0.5064
• F1 1 Not Happening: 0.6036
• F1 2 Not Human: 0.3804
• F1 3 Not Bad: 0.4901
• F1 4 Solutions Harmful Unnecessary: 0.3382
• F1 5 Science Is Unreliable: 0.4126
• F1 6 Proponents Biased: 0.4433
• F1 7 Fossil Fuels Needed: 0.4752

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: 22
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 7
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	F1 0 Not Relevant	F1 1 Not Happening	F1 2 Not Human	F1 3 Not Bad	F1 4 Solutions Harmful Unnecessary	F1 5 Science Is Unreliable	F1 6 Proponents Biased	F1 7 Fossil Fuels Needed
0.4502	1.0	2324	0.2539	0.9214	0.9208	0.9256	0.9214	0.8674	0.8627	0.9116	0.9473	0.9461	0.9092	0.9277	0.9683
0.3061	2.0	4648	0.1701	0.9446	0.9447	0.9461	0.9446	0.8858	0.9185	0.9295	0.9574	0.9628	0.9450	0.9446	0.9750
0.1339	3.0	6972	0.2239	0.9499	0.9499	0.9502	0.9499	0.8900	0.9412	0.9506	0.9469	0.9611	0.9506	0.9364	0.9786
0.0217	4.0	9296	0.3198	0.9517	0.9517	0.9520	0.9517	0.9073	0.9430	0.9520	0.9561	0.9542	0.9537	0.9369	0.9771
0.0032	5.0	11620	0.3009	0.9530	0.9530	0.9531	0.9530	0.9007	0.9408	0.9553	0.9565	0.9602	0.9525	0.9388	0.9815
0.0001	6.0	13944	0.3055	0.9538	0.9537	0.9537	0.9538	0.9055	0.9424	0.9536	0.9590	0.9589	0.9540	0.9413	0.9802
0.0028	6.9972	16261	0.3108	0.9529	0.9529	0.9529	0.9529	0.9055	0.9413	0.9541	0.9574	0.9564	0.9541	0.9403	0.9792

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0