self_iterative_v2_targeted_iteration_1

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

• Loss: 6.5896
• Accuracy Targeted: 0.6822
• F1 Macro Targeted: 0.4884
• F1 Weighted Targeted: 0.6003
• F1 Macro Total: 0.4884
• F1 Weighted Total: 0.6003

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: 6e-06
• train_batch_size: 4
• eval_batch_size: 4
• seed: 1337
• 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: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Targeted	F1 Macro Targeted	F1 Weighted Targeted	F1 Macro Total	F1 Weighted Total
0.3375	1.0	5899	4.8907	0.6778	0.4040	0.5476	0.4040	0.5476
0.2568	2.0	11798	4.9433	0.6778	0.4040	0.5476	0.4040	0.5476
0.2147	3.0	17697	5.5877	0.6889	0.4516	0.5799	0.4516	0.5799
0.1024	4.0	23596	6.9925	0.6733	0.4271	0.5607	0.4271	0.5607
0.1134	5.0	29495	6.5896	0.6822	0.4884	0.6003	0.4884	0.6003
0.0407	6.0	35394	7.8903	0.6733	0.4694	0.5863	0.4694	0.5863
0.024	7.0	41293	6.2429	0.6756	0.4451	0.5722	0.4451	0.5722
0.0105	8.0	47192	9.8105	0.68	0.4360	0.5679	0.4360	0.5679
0.0334	9.0	53091	9.7531	0.6689	0.4194	0.5547	0.4194	0.5547
0.0161	10.0	58990	11.4841	0.6667	0.4408	0.5672	0.4408	0.5672

Framework versions

• Transformers 4.50.2
• Pytorch 2.6.0+cu124
• Datasets 3.0.1
• Tokenizers 0.21.1